Nasal and oral respiration sensor

ABSTRACT

An apparatus having a support structure, including two nasal flow passages aligned with one another and with respect to a nasal respiratory flow direction, and an oral flow passage disposed transverse to the two nasal flow passages, along an oral respiratory flow direction, the nasal flow passages and oral flow passages having thermistors to monitor a patient&#39;s respiration, and the apparatus having a thermistor for monitoring ambient conditions and an accelerometer for monitoring movement of the apparatus. The apparatus also detecting and distinguishing between oral and individual nasal air flows, and integration of the apparatus and monitored data with a network.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation-in-part of U.S. patentapplication Ser. No. 16/218,388 entitled “NASAL AND ORAL RESPIRATIONSENSOR,” filed on Dec. 12, 2018, which claims the benefit of U.S. PatentApplication No. 62/597,870, filed on Dec. 12, 2017, the entirety ofwhich is incorporated herein by reference.

BACKGROUND

The present disclosure relates generally to medical sensors. Moreparticularly, the present disclosure relates to respiration sensors fora continuous, long-lasting monitoring of an individual or patient,including measuring and analyzing respiratory condition and movement ofthe person.

The respiration of a person may be monitored for various reasons. Forexample, knowledge about a patient's respiration may assist a caregiverin assessing the patient's stability during surgery and recoverythereafter. Knowledge about a person's respiration can also assist withtherapy related to sleeping.

Many approaches to respiration sensors involve cumbersome devices thatcan obstruct a patient's respiratory passages. In many applications, thepatient is unconscious or semi-conscious and there is a challenge to fixa respiration sensor in place for an extended period of time.Accordingly, in many of the existing systems a nurse is required tofrequently check the patient for sensor placement or inadvertent sensormovement. Moreover, due to the physiognomy of the human respiratorypassages, many devices tend to produce confused readings relative toeither of a patient's nostrils and mouth, and fail to clearlydistinguish and provide differentiated data for inspiration andexhalation steps.

SUMMARY

In the field of medical care for patients with respiratory dysfunction,it is highly desirable to provide continuous, real-time measurement ofthe patient's respiratory cycles. In the measurement of respiratorycycles from patients, one of the challenges is to clearly distinguishbetween inhalation and exhalation cycles. The complication is compoundedby the human physiognomy, which places nasal and oral flows (in and outof the patient) in close proximity to each other, thereby increasing thepossibility of flow mix, turbulence, and stagnation in some places.

An aspect of the present disclosure provides, but is not limited to, arespiration sensor for monitoring and analysis of an individual orpatient's respiratory condition and cycle, monitoring and analysis toensure a respiration sensor is positioned as intended, detectingmovement of a person using a respiration sensor, detecting anddistinguishing between oral and individual nasal air flows, andintegration of a respiration sensor and data with a network.

In some embodiments, the present disclosure provides a respirationsensor comprising: a housing having a nasal flow passage that extendstherethrough, wherein the nasal flow passage is disposed approximatelyparallel with a nasal respiratory flow direction; and an electronicsboard comprising a nasal thermistor, the electronics board coupled tothe housing such that the nasal thermistor is positioned into the nasalflow passage.

In some embodiments, a respiration sensor is disclosed, the respirationsensor comprising: a housing having a first nasal flow passage and asecond nasal flow passage that extend therethrough, wherein the nasalflow passages are disposed in parallel to one another with respect to anasal respiratory flow direction; and an electronics board comprising afirst nasal thermistor and a second nasal thermistor, the electronicsboard coupled to the housing such that the first and second nasalthermistors are positioned into each of the first and second nasal flowpassages, respectively.

In some embodiments, the present disclosure provides a respirationsensor comprising: one or more thermistors configured to detect at leastone of an inspiratory temperature, an expiratory temperature, an ambienttemperature adjacent the respiratory sensor, or a temperature of apatient's skin engaged against the respiratory sensor; an accelerometerconfigured to detect at least one of a movement of the patient, aposition of the patient, a heart rate, or a respiration rate; and anelectronics board coupled to the one or more thermistors and the one ormore thermistors.

In some embodiments, the present disclosure provides a system,comprising: a server having a memory storing commands, and a processorconfigured to execute the commands to: receive, from a hub, a dataindicative of a respiratory condition of a patient; transfer the datainto a memory in a remote server; provide the data to a mobile computerdevice, upon request; and instruct the mobile computer device tographically display the data, wherein the data comprises a temperaturevalue from at least one of two nasal flow passages, a temperature valuefrom an oral flow passage, a temperature value of a patient's skinsurface, and a temperature value of a patient's environment.

In some embodiments of the present disclosure, a method is disclosed,the method comprising: receiving, from a hub, a data indicative of arespiratory condition of a patient; transferring the data into a memoryin a remote server; providing the data to a monitor, upon request; andinstructing the monitor to graphically display the data, wherein thedata comprises a temperature value from at least one of two nasal flowpassages, a temperature value from an oral flow passage, a temperaturevalue of a patient's skin surface, and a temperature value of apatient's environment.

In some embodiments a respiration sensor system is disclosed, therespiration sensor system comprising: a respiration sensor comprising ahousing having a nasal flow passage that extends therethrough, whereinthe nasal flow passage is aligned with a nasal respiratory flowdirection, and an electronics board comprising a nasal thermistor, theelectronics board coupled to the housing such that the nasal thermistoris positioned into the nasal flow passage; and a hub configured to movedata between the respiration sensor and a network.

Additional features and advantages of the subject technology will be setforth in the description below, and in part will be apparent from thedescription, or may be learned by practice of the subject technology.The advantages of the subject technology will be realized and attainedby the structure particularly pointed out in the written description andembodiments hereof as well as the appended drawings.

It is to be understood that both the foregoing general description andthe following detailed description are exemplary and explanatory and areintended to provide further explanation of the subject technology.

BRIEF DESCRIPTION OF THE DRAWINGS

Various features of illustrative embodiments of the inventions aredescribed below with reference to the drawings. The illustratedembodiments are intended to illustrate, but not to limit, theinventions. The drawings contain the following figures.

FIG. 1 illustrates a front perspective view of a respiration sensorplaced on a patient's head, according to some embodiments.

FIG. 2A illustrates a side plan view of a gas flow exiting from apatient's nasal cavity, according to some embodiments.

FIG. 2B illustrates a side plan view of a gas flow exiting from apatient's oral cavity, according to some embodiments.

FIG. 3 illustrates a front plan view of a gas flow exiting from apatient's nasal cavity, according to some embodiments.

FIG. 4 illustrates a front perspective view of nasal respiration flowsand oral respiration flows in a patient, according to some embodiments.

FIG. 5 illustrates a front perspective view of a respiration sensorincluding nasal flow passages and oral flow passages, according to someembodiments.

FIG. 6 illustrates perspective detail views of nasal flow passages andoral flow passages of a respiration sensor, according to someembodiments.

FIG. 7 illustrates a cross-sectional view of a laminar respiration flowrelative to a thermistor in a respiration sensor, according to someembodiments.

FIG. 8 illustrates a schematic view of a flow passage of a respirationsensor, according to some embodiments.

FIGS. 9A and 9B illustrate front and back perspective views of arespiration sensor, according to some embodiments.

FIG. 10 illustrates a front perspective view of a respiration sensorplaced on a patient's head, according to some embodiments.

FIG. 11 illustrates a front perspective view of a respiration sensor,according to some embodiments.

FIG. 12 illustrates a bottom perspective view of the respiration sensorof FIG. 11.

FIG. 13 illustrates a front perspective detail view of a respirationsensor, according to some embodiments.

FIG. 14 illustrates a front perspective cross-sectional view of therespiration sensor of FIG. 11.

FIG. 15 illustrates a schematic view of a nasal respiration flow and anasal flow guide, according to some embodiments.

FIG. 16 illustrates a schematic view of a nasal flow guide, according tosome embodiments.

FIG. 17 illustrates a back perspective view of a respiration sensor,according to some embodiments.

FIG. 18 illustrates a schematic view of a respiration flow through acavity of a respiration sensor, according to some embodiments.

FIG. 19 illustrates a schematic view of turbulent respiration gas flowthrough a cavity of a respiration sensor, according to some embodiments.

FIG. 20 illustrates a graph showing turbulent noise flow duringexpiration, according to some embodiments.

FIGS. 21A and 21B illustrate front and side plan views of exit anglesfor a gas flow exiting from a patient's nasal cavity, according to someembodiments.

FIGS. 22A and 22B illustrate front and side schematic views of aposition of an oral cavity relative to a patient, according to someembodiments.

FIG. 23 illustrates a front perspective view of a respiration sensor,according to some embodiments.

FIG. 24 illustrates a graph showing measurements for the respirationsensor of FIG. 23 for different patients, according to some embodiments.

FIGS. 25A and 25B illustrates a front plan views of positions of an oralcavity for a respiration sensor relative to a mouth of differentpatients, according to some embodiments.

FIG. 26 illustrates a front perspective view of a respiration sensorhaving a strap, according to some embodiments.

FIG. 27 illustrates a front perspective view of a respiration sensorhaving a band, according to some embodiments.

FIG. 28 illustrates a front perspective exploded view of a respirationsensor, according to some embodiments.

FIG. 29 illustrates a top perspective detail view of an electronicsboard and frame of a respiration sensor, according to some embodiments.

FIG. 30 illustrates a top perspective view of an electronics board of arespiration sensor, according to some embodiments.

FIG. 31 illustrates a top perspective detail view of the electronicsboard of FIG. 30, according to some embodiments.

FIG. 32 illustrates a bottom perspective view of the electronics boardof FIG. 30, according to some embodiments.

FIG. 33 illustrates a top perspective view of the electronics board ofFIG. 30 coupled with a frame and a battery, according to someembodiments.

FIG. 34 illustrates a block diagram of an electronics board of arespiration sensor, according to some embodiments.

FIG. 35 illustrates another block diagram of an electronics board of arespiration sensor, according to some embodiments.

FIG. 36 illustrates a respiration sensor detection state table fordetermining the respiration sensor placement and function, according tosome embodiments.

FIG. 37 illustrates a graph showing breathing during changes in ambientair temperature, according to some embodiments.

FIG. 38 illustrates a graph showing breathing during conductingtemperature changes, according to some embodiments.

FIG. 39 illustrates a respiration sensor in use on a patienttransitioning from a seated position, to a moving position, to a fallenposition, according to some embodiments.

FIG. 40 illustrates a front plan view of a heart and directions of bloodcirculation therethrough.

FIG. 41 illustrates a front plan view of a respiration sensor includingan accelerometer for detecting body movement of a patient utilizing therespiration sensor, according to some embodiments.

FIG. 42 illustrates a front perspective exploded view of a respirationsensor having EtCO2 sensitive surfaces, according to some embodiments.

FIG. 43 illustrates a schematic view of a respiration monitoring system,according to some embodiments.

FIG. 44 illustrates a front perspective view of a respiration sensorcoupled to a patient and a hub adjacent to the patient according to someembodiments.

FIG. 45 illustrates a front perspective view of a respiration sensor andhub coupled to a patient, according to some embodiments.

FIG. 46 illustrates perspective detail views of an interaction between arespiration sensor and a hub in a respiration monitoring system,according to some embodiments.

FIG. 47 illustrates a front perspective view of a respiration sensor andhub coupled with a headdress, according to some embodiments.

FIG. 48 illustrates a side view of a respiration sensor and hub coupledwith another headdress, according to some embodiments.

FIG. 49 illustrates a front perspective view of a smartphone as amonitor for a respiration monitoring system, according to someembodiments.

FIG. 50 illustrates a front perspective view of a central station asanother monitor for a respiration monitoring system, according to someembodiments.

FIG. 51 is a flow chart of an example method of a sensor devicedetecting a physiological parameter and initiating a pairing processwith a monitoring device, according to illustrative implementations.

FIG. 52 is a flow chart of an example method of a sensor devicedetermining a color for the sensor device, according to illustrativeimplementations.

FIG. 53 is a flow chart of an example method of a sensor deviceassociating a new monitoring device with a patient, according toillustrative implementations.

FIG. 54 is a flow chart of an example method of a pairing process with asensor device at a monitoring device, according to illustrativeimplementations.

FIG. 55 is a flow chart of an example method of a monitoring devicedetermining a color for a patient, according to illustrativeimplementations.

FIG. 56 is a flow chart of an example method of detecting speech by apatient, according to illustrative implementations.

FIG. 57 is a flow chart of an example method of displaying a position ofa sensor device on a patient, according to illustrative implementations.

FIG. 58 is a flow chart of an example method of displaying movement of asensor device on a patient in real-time in a user interface, accordingillustrative implementations.

FIG. 59 is a flow chart of an example method of a monitoring devicedetecting a sleep apnea of a patient, according to illustrativeimplementations.

FIG. 60 is a flow chart of an example method of a monitoring devicedetermining whether a patient is in compliance with instructions of aclinician, according to illustrative implementations.

FIG. 61 is a flow chart of an example method of a detecting nasal cavityconditions based on received breathing pattern data, according toillustrative implementations.

FIG. 62 is a flow chart of an example method of adjusting a userinterface of a monitoring device, according to illustrativeimplementations.

FIG. 63 is a flow chart of an example method of predicting a likelihoodof a chronic obstructive pulmonary disease (COPD) exacerbation,according to illustrative implementations.

FIG. 64 is a flow chart of an example method of determining an activitylevel of a patient and associating the activity level with one or morebaseline physiological values, according to illustrativeimplementations.

FIG. 65 is a flow chart of an example of determining a path traveled bythe patient and associating the path with one or more baselinephysiological values, according to illustrative implementations.

FIG. 66A illustrates an example graphical representation of a boundedarea displaying graphical representations of paths travelled by apatient, according to illustrative implementations.

FIG. 66B illustrates an example graphical display of real timemeasurements for indicating whether a patient is likely to experience ahealth event, according to illustrative implementations.

FIG. 66C illustrates another example graphical display of real timemeasurements for indicating whether a patient is likely to experience ahealth event, according to illustrative implementations.

FIG. 67 illustrates a side perspective detail view of an electronicsassembly of a sensor device, according to illustrative implementations.

FIG. 68 illustrates a side perspective detail view of an electronicsboard of a sensor device, according to illustrative implementations.

FIG. 69 illustrates a side perspective detail view of an electronicsboard of a sensor device, according to illustrative implementations.

In the figures, elements having the same or similar reference numeralhave the same or similar functionality or configuration, unlessexpressly stated otherwise.

DETAILED DESCRIPTION

It is understood that various configurations of the subject technologywill become readily apparent to those skilled in the art from thedisclosure, wherein various configurations of the subject technology areshown and described by way of illustration. As will be realized, thesubject technology is capable of other and different configurations andits several details are capable of modification in various otherrespects, all without departing from the scope of the subjecttechnology. Accordingly, the summary, drawings, and detailed descriptionare to be regarded as illustrative in nature and not as restrictive.

The detailed description set forth below is intended as a description ofvarious configurations of the subject technology and is not intended torepresent the only configurations in which the subject technology may bepracticed. The appended drawings are incorporated herein and constitutea part of the detailed description. The detailed description includesspecific details for the purpose of providing a thorough understandingof the subject technology. It will be apparent, however, to oneordinarily skilled in the art that the embodiments of the presentdisclosure may be practiced without some of these specific details. Inother instances, well-known structures and components are shown in blockdiagram form in order to avoid obscuring the concepts of the subjecttechnology, or have not been shown in detail so as not to obscure thedisclosure. Like components are labeled with similar element numbers forease of understanding.

In accordance with at least some embodiments disclosed herein isrespiration sensor that can: monitor nasal and oral respiration gasflow; monitor patient and ambient conditions; monitor movement of therespiration sensor; distinguish between oral and nasal air flow, andbetween left and right nasal air flow. The respiration sensor canidentify and analyze thermal transfer distinction between inhalation andexhalation gases to provide a clear pattern of the respiratory cycle.

In at least some embodiments disclosed herein, any of nasal and oralrespiration gas flow, heart rate, respiration rate or cycle, andmovement of the respiration sensor and patient are determined.Embodiments of the present disclosure can send and receive data relatedto the monitoring and analysis by the respiration sensor; indicate apatient's condition or position; and provide a signal or alarmcorresponding to specific conditions. In some embodiments, wirelesscommunication techniques are utilized to provide ubiquitous solutionsfor respiratory sensing of patients in hospitals, treatment facilities,home-care situations, and the like.

I. Embodiments of Respiratory Sensors

FIG. 1 illustrates a respiration sensor 10 placed on a patient's head20, according to some embodiments. The respiration sensor 10 ispositioned on patient's face between the mouth and nose to measure nasaland oral breathing gas flow. The gas flow measurement is based onmeasuring temperature differences between inspiratory and expiratory gasflows. Patient's skin and ambient air temperatures can also be measuredto verify that the respiration sensor 10 is placed appropriately againstthe patient. Some embodiments, later described, include other sensors,such as capacitive sensors or detectors and accelerometers to ensurethat respiration sensor 10 has not fallen out of place, and thatrespiration sensor 10 is making proper contact with the patient'sphysiognomy. A securement string or strap 15 helps maintain the positionof respiration sensor 10 relative to the patient's physiognomy.

FIGS. 2A and 3 illustrate regions 200 a, 200 c for a gas flow exitingfrom a patient's nasal cavities, and FIG. 2B illustrates regions 200 bfor a gas flow exiting from a patient's oral cavity, according to someembodiments. Experiments show that breathing gas flow exits nasal andoral cavities in different regions between different subjects.Accordingly, embodiments of a respiration sensor as disclosed hereininclude a geometry that may separate each of the different flows throughthe regions 200 a, 200 b, 200 c to provide a more accurate measure ofthe respiratory cycles of a patient. Accordingly, a precisedetermination of the positioning of the respiration sensor 100 a, 100 brelative to the patient's face is highly desirable.

FIG. 4 illustrates a portion of nasal respiration flow 600C and oralrespiration flow 600B for a patient 20, according to some embodiments.Sensor cavities of the respiration sensor capture nasal and oralbreathing gas flow from the patient. The sensor cavities are positionedparallel to the average direction of that specific flow to maintain flowas laminar as possible inside the cavity. Thus, nasal sensor cavitiesare positioned parallel to each other between the nose and mouth, butalso parallel to upper lip. More advantageously, nasal sensor cavitiesslightly diverge past the middle part of the mouth and upper lip intothe average direction of nasal breathing gas flows. An oral sensorcavity is positioned transverse to the nasal cavities, outwards from themouth. In some embodiments, the oral sensor cavity and the nasal sensorcavities are positioned relative to each other so that a direction oforal respiration flow 600B through the oral cavity is transverserelative to a direction of nasal respiration flow 600C through any ofthe nasal sensor cavities. Sensor cavities are also smooth and straight,or more advantageously slightly tapered, to capture flow from a largerarea, since any turn or sudden change in the cross-section of cavityalong the flow path generate turbulences that mix inspiratory andexpiratory air flow phases degrading the measurement speed, accuracy andresponse time.

FIG. 5 illustrates a respiration sensor 100 a, for example, includingnasal flow passages 301 and an oral flow passage 302. The nasalrespiration flow exiting a patient's nasal cavity, e.g., gas flowregions 200 a, 200 c, can be captured and guided by a nasal passage 301parallel to average direction of nasal respiration flow 600C. Similarly,the oral respiration flow exiting a patient's mouth, e.g., gas flowregion 200 b, can be captured and guided by the oral cavity 302 parallelto direction of the oral respiration flow 600B. By providing a sensingelement inside of each of the different flow passages 301 and 302, therespiration sensor 100 a may accurately determine a respiration flowbefore the nasal flow and the oral flows are mixed together adjacent thepatient's upper lip.

FIG. 6 illustrates the respiration sensor 100 a, with portions thereofshown in detail views, including detail views of the nasal flow passages301 and the oral flow passage 302. The respiration sensor 100 a includesthermistors 400-1, 400-2, 400-3 for sensing inhalation and exhalationflows. A nasal respiratory flow of a patient can be captured by thenasal passages 301 and measured with a first and second nasalthermistors 400-1, 400-2 therein. An oral respiratory flow of thepatient can be captured by the oral cavity 302 and measured withthermistor 400-3 therein. The resistance of each thermistor changesproportionally to flowing gas heating or cooling down the thermistor,e.g., during inspiration and expiration.

Moreover, the nasal flow passages 301 are separated from each other suchthat nasal thermistors 400-1 and 400-2 may separately identify andmeasure the respiration flow associated with each of the patient'snostrils. By separately identifying respiration flow associated witheach of the patient's nostrils, potential respiratory conditions orpatient's positions can be determined. For example, a blockage of anasal passage or the respiration device can be identified and corrected.

In some embodiments, oral thermistor 400-3 is placed on a plane that istransverse or substantially perpendicular to nasal thermistors 400-1,400-2. This geometry also enables an accurate and independentmeasurement between each of the thermistors 400-1, 400-2, 400-3,avoiding any mixing or turbulent area.

Referring to FIGS. 7 and 8, the thermistors 400-1, 400-2, 400-3 can belocated approximately in the middle of its corresponding sensor cavityto maximize accuracy and sensitivity to gas flows. To position thethermistor 400-1, 400-2, 400-3 in the middle of a corresponding sensorcavity, the thermistor 400-1, 400-2, 400-3 is coupled to a tip portionof a thin support structure 730. The support structure can have aproximal portion coupled to an electronics board and a distal portiontransverse to a plane defined by the top of the electronics board,wherein the distal portion of the support structure extends into a nasalflow passage. In some embodiments, the respiration sensor 100 a has astructure and geometry that separates the nasal flow from each nostrilseparately, to provide a more accurate and detailed picture of thepatient's respiratory condition.

FIG. 7 illustrates a cross-section of a laminar respiration flow of apatient through a sensor cavity. Laminar flow speed distribution in atube is parabolic, thus the speed is maximum at a point approximately inthe middle of the tube. The respiration flow is illustrated relative tothermistor 400-1 of a respiration sensor 100 a, however, the presentdisclosure can apply to any thermistor 400-1, 400-2, 400-3. By placingthermistor 400-1 as close as possible to the middle of the flow cavityin the respiration sensor 100 a, for example, a more accuratemeasurement is expected, as the velocity of the gas flow is highest atthe center of the flow cavity. Accordingly, it is expected that atemperature differential between inhalation and exhalation be highest atthe middle point of the flow cavity. Moreover, the convection orradiated thermal energy from surrounding structures is minimized when athermistor 400-1, 400-2, 400-3 is located into the middle of cavity by asupport structure 730.

FIG. 8 illustrates the respiration sensor 100 a, with a portion thereofshown in a cross-sectional detail view. The cross-sectional viewillustrates a support structure 730 extending into the nasal flowpassage 301, and the thermistor 400-1 positioned at a distal end portionof the support structure 730. It should be understood that the presentdisclosure, including support structures, can apply to any of thethermistors 400-1, 400-2, 400-3 and flow passages 301, 302.

The support structure 730 extends from a portion of the respirationsensor 100 a into the nasal flow passage 301. It should be understoodthat the support structure 730 can extend partially into a flow passage301, 302. For example, the support structure 730 can extend into amid-portion of at least one of the two nasal flow passages 301. In someembodiments of the present disclosure, the support structure 730 extendsbeyond or across the respective flow passage 301, 302. The supportstructure 730 can comprise a cantilevered structure that extends into arespective flow passage 301, 302. However, in some embodiments, thesupport structure 730 can comprise an arch structure partially extendingaway from an inner surface of the flow passage 301, 302 toward thethermistor 400-1, and partially extending from the thermistor 400-1toward the inner surface of the flow cavity. In some embodiments, thesupport structure 730 and the thermistor 400-1 can extend across innersurfaces of the flow cavity.

The respiration sensor 100 a includes walls having an inner surfaceforming the sensor cavities. The walls of the cavity extend around atleast a portion of the thermistors 400-1, 400-2, 400-3. The wallsprotect the sensitive thermistors 400-1, 400-2, 400-3 from variousdisturbing ambient gas flows causing error to measured breathing gasflow signal, for example, a caregiver being able to touch or breatheinto thermistors or air conditioning in proximity to the thermistor400-1, 400-2, 400-3. In addition, the walls forming the cavities alsoprotect small, mechanically sensitive thermistors from variousmechanical forces, stresses, and shocks, such as touching etc.

FIGS. 9A and 9B illustrate the respiration sensor 100 a, for example,including thermistors 500-1, 500-2 for sensing the positioning of thesensor relative to a patient's physiognomy, according to someembodiments. An ambient thermistor 500-1 can be positioned along a frontside of the respiration sensor 100 a, adjacent a portion of therespiration sensor 100 a that faces away from the patient when therespiration sensor 100 a is worn by a patient. Similarly, a skinthermistor 500-2 can be positioned along a back side of the respirationsensor 100 a, adjacent a portion of the respiration sensor 100 a thatfaces toward the patient when the respiration sensor 100 a is worn by apatient. In some embodiments, when the respiration sensor 100 a is wornby a patient, the thermistor 500-1 is distal to the patient's face, andthe thermistor 500-2 is proximal to the patient's upper lip and engagedagainst the patient's skin.

The respiration sensor 100 a can include a passage or cavity along anyof the front side or the back side thereof. The thermistor 500-1 can bepositioned in a cavity along the front side of the respiration sensor100 a to measure ambient air temperature. The thermistor 500-2 can bepositioned in a cavity along the back side of the respiration sensor 100a to measure the temperature of patient's skin.

In some instances, thermistor 500-2 can detect when the sensor 100 a isproperly positioned on the patient while thermistor 500-1 can detect thetemperature of ambient air. Comparison of temperatures from 500-1 and500-2 can be used to indicate a patient condition or proper positioningand function of the sensor 100 a, for example. In some embodiments, whenthermistors 500-1 and 500-2 detect the same temperature, it may beassumed that respiration sensor 100 a is likely not attached to thepatient, or that the patient's temperature is the same as the ambienttemperature, which may indicate a hazardous health condition.

FIG. 10 illustrates another embodiment of a respiration sensor 100 b,which is substantially similar to respiration sensor 100 a. Respirationsensor 100 b is also placed on a patient's face between the mouth andnose to measure nasal and oral breathing gas flows. Much like therespiration sensor 100 a, the measurement is based on measuringtemperature differences between inspiratory and expiratory gas flows.The patient's skin temperature and the ambient air temperature can alsobe measured to verify or detect that the respiration sensor 100 b isplaced appropriately with respect to the patient's nasal and oralbreathing gas flows and to the patient's upper lip.

Some embodiments described herein include other sensors, such ascapacitive detectors or sensors to detect whether the respiration sensor100 b is making proper contact with the patient's physiognomy andaccelerometers to detect movement and position of the respiration sensor100 b to ensure, for example, that the respiration sensor 100 b has notfallen out of place, that the patient has not fallen down, or that theorientation of the patient's head is not obstructing the nasal and oralbreathing gas flows (e.g., patient's face is downward towards pillow orbed).

A string or strap 150 b helps maintain the position of the respirationsensor 100 b relative to the patient's physiognomy. According to someembodiments, the respiration sensor 100 b can include a nasal flow guide160 to concentrate and provide laminar inspiratory and expiratory gasflows through the respiration sensor 100 b.

FIGS. 11 and 12 illustrate the respiration sensor 100 b having a housing2001, a base 2010, and a shroud 2012. The shroud 2012 is positionedbetween the housing 2001 and the base 2010 to form at least a portion ofa cavity. The respiration sensor 100 b includes nasal flow passages2018, which are similar to nasal flow passages 301, and an oral flowpassage 2016, which is similar to oral flow passages 302 of respirationsensor 100 a. The nasal flow passages 2018 extend from a top portion toa bottom portion of the respiration sensor 100 b. In use, a nasalrespiration flow from a patient's nose can move between the nasal inlet2024 and the nasal outlet 2026 of each of the nasal flow passages 2018.The nasal inlet 2024 of each of the nasal flow passages 2018 is wherethe breathing gas flows into the respiration sensor 100 b duringexpiration. The nasal outlet 2026 of each of the nasal flow passages2018 is where the ambient air flows into the respiration sensor 100 bduring inspiration.

The shroud 2012 includes a battery frame 2014, which extends away from afront surface of the shroud 2012. The battery frame 2014 encloses abattery, securing it to the base 2010 and divides the area between theshroud 2012 and the housing 2001 into two distinct nasal flow passages2018, such that the nasal thermistor 400-1 is centrally disposed in oneof the nasal flow passages 2018 and the nasal thermistor 400-2 iscentrally disposed in the other one of the nasal flow passages 2018. Thebattery frame 2014 is disposed substantially centrally on therespiration sensor 100 b and is arranged to be positioned under theseptum of a patient's nose when the respiration sensor 100 b is placedon or attached adjacent to the upper lip of the patient.

Housing 2001 can be made of a paper battery engineered to use a spacerformed largely of cellulose that makes paper batteries flexible andenvironmentally-friendly. The functioning is similar to conventionalchemical batteries with the important difference that they arenon-corrosive and do not require extensive housing, but can function ashousing.

An oral shroud 2017 extends from the shroud 2012, and includes a passagethrough a distal portion thereof. The passage forms an oral flow passage2016 having a thermistor 400-3 positioned therein. The oral flow passage2016 is arranged such that the oral thermistor 400-3 is centrallydisposed within the oral flow passage 2016. In use, an oral respirationflow from a patient's mouth can move between the oral inlet 3036 and theoral outlet 2038.

FIG. 13 illustrates an embodiment the respiration sensor 100 b, showingthe base 2010 and the shroud 2012, with the housing 2001 omitted forclarity. The shroud 2012 encloses an electronics board, securing it tothe base 2010. The thermistors 400-1, extend from the electronics boardthrough the shroud 2012. The thermistors 400-1, 400-2 are oriented suchthat a distal portion of the thermistors 400-1, 400-2 extend into aspace forming the nasal cavities 1301 when the shroud 2012 and thehousing 2001 are coupled together.

The respiration sensor 100 b can include a light-emitting diode (LED)2013, which is visible through the shroud 2012. The LED 2013 can providea confirmation or an indication of status. For example, the LED 2013 canindicate when the respiration sensor 100 b is paired with anotherdevice. In some embodiments, the LED 2013 can indicate any of a chargedor low battery, an indication that the respiration sensor 100 b isfunctioning as intended, or an indication that there is a detectedproblem with the respiration sensor 100 b. The LED 2013 can be used toindicate the location of the patient for example in hospital PACU wherethere are many patients, respiration sensors and monitoring devices inthe same room. The LED 2013 can be turned on or display a series ofblinks from the monitoring device to indicate the location of thepatient and the connected respiration sensor. This may be important toensure that a caregiver is looking at the correct monitoring deviceconnected to patient and the respiration sensor. It should be understoodthat any embodiment of the respiration sensor, such as respirationsensor 100 a, 100 b, can include an LED 2013.

In some embodiments, a spacer 2019 can be positioned between the batteryand a battery contact. The spacer 2019 can maintain the battery contactspaced apart from the battery, thereby preventing electrical conductiontherebetween. The spacer 2019 can prevent discharge of the batterybefore the respiration sensor 100 b is intended to be used. When therespiration sensor 100 b is intended to be used, the spacer 2019 can beremoved or separated from the respiration sensor 100 b. In someembodiments, the respiration sensor 100 b can comprise an opening orpassage 2015 that extends between the battery and an outer surface ofthe housing 2001 or the shroud 2012. The spacer 2019 can be movedthrough the passage 2015 to separate the spacer 2019 from therespiration sensor 100 b. In some embodiments, the spacer 2019 maycomprise a plastic material in the form or a strip or tape.

FIG. 14 illustrates an embodiment the respiration sensor 100 b, showingthe base 2010, the shroud 2012, and the flow guides 160, with a portionof the housing 2001 and other features omitted for clarity. At least onenasal flow guide 160 is disposed in each of the nasal flow passages 2018and extends between the shroud 2012 and the housing 2001, as shown in atleast FIGS. 11 and 12.

In some embodiments, at least one nasal flow guide 160 is disposedproximate a nasal inlet 2024 of each of the nasal flow passages 2018 andat least one nasal flow guide 160 is disposed within each of the nasalflow passages 2018. A nasal flow guide 160 can be positioned in a nasalflow passage, proximate any of the nasal inlet 2024 and the nasal outlet2026. The nasal flow guide 160 is aligned relative to the nasalthermistor 400-1 or 400-2 to direct a flow of gas toward relative to thenasal thermistor 400-1 or 400-2.

FIGS. 14 and 15 illustrates flow of gases relative to the respirationsensor 100 b, a patient's nares, and the ambient environment. Arrows2028 illustrate a portion of nasal respiration flow from a patient'snares toward the nasal thermistor 400-1, 400-2 during expiration, andarrows 2029 illustrate a portion of ambient gas directed from theambient environment toward the nasal thermistor 400-1, 400-2 duringinspiration.

In more detail, during expiration, the at least one nasal flow guide160, disposed proximate the nasal inlet 2024 guides the breathing gasflow through the nasal flow passages 2018 of the respiration sensor 100b and concentrates the breathing gas flow toward each of the nasalthermistors 400-1, 400-2 while maintaining the breathing gas flowlaminar as it passes each of the nasal thermistors 400-1, 400-2 tominimize turbulent noise. Similarly, during inspiration, the at leastone nasal flow guide 160 disposed proximate the nasal outlet 2026 guidesthe ambient air flow through the nasal flow passages 2018 of therespiration sensor 100 b and concentrates the ambient air flow towardeach of the nasal thermistors 400-1, 400-2 while maintaining the ambientair flow laminar as it passes each of the nasal thermistors 400-1, 400-2to minimize turbulent noise.

The at least one nasal flow guide 160 can prevent undesired objects fromentering the nasal flow passages 2018 and disturbing or breaking thenasal thermistors 400-1, 400-2 and/or their associated supportstructures. The at least one nasal flow guide 160 can also form an airgap around the nasal thermistors 400-1, 400-2 with respect to thehousing 2001 and the at least one nasal flow guide 160, which preventselectro static discharge (ESD) from entering the electronics board 300via the nasal thermistors 400-1, 400-2 and their associated supportstructures.

In some embodiments, the at least one nasal flow guide 160 includes athickness that is less than 1 mm and a height that is more than 2 mm. Insome embodiments, two or four nasal flow guides 160 are disposed withineach of the nasal flow passages 2018 proximate the nasal inlet 2024and/or two or four nasal flow guides are disposed within each of thenasal flow passages 2018 proximate the nasal outlet 2026. In someembodiments, the number of nasal flow guides 160 does not exceed five toallow for proper gas flow through the nasal flow passages 2018.

FIG. 16 illustrates a schematic view of a nasal respiration flow guidegrid 2030. The flow guide grid 2030 can function similarly to flow guide160, wherein a flow of gas through a cavity of the respiration sensor100 b is directed by the flow guide grid 2030. The flow guide grid 2030can have walls which intersect and are transverse relative to eachother. In some embodiments, a flow guide grid 2030 is disposed proximatethe nasal inlet 2024 and a flow guide grid 2030 is disposed proximatethe nasal outlet 2026 of each nasal cavity of the nasal flow passages2018.

Additional sensors of a respiration sensor 100 b are illustrated in theback, perspective view of the respiration sensor 100 b in FIG. 17. Therespiration sensor 100 b includes a thermistor 500-2 and a sensor 1401located on the back portion of the respiration sensor 100 b. Thethermistor 500-2 can provide temperature information regarding thepatient or an ambient environment adjacent to the back portion of therespiration sensor 100 b. The sensor 1401 is a capacitive plate, whichcan engage against the patient. The sensor 1401 can engage against aregion between a patient's upper lip and nose, e.g., an area includingthe philtrum, and provide information to determine a location of therespiration sensor 100 b relative to the patient's face.

II. Gas Flow Through Respiration Sensors

Referring to FIGS. 17 and 18, an oral shroud 2017 of the respirationsensor 100 b can have a cross-sectional area that tapers along a portionthereof or relative to an oral inlet 2036 and an oral outlet 2038. Theoral inlet 2036 is where the breathing gas flows into the oral flowpassage 2016 of the respiration sensor during expiration, and the oraloutlet 2038 is where the ambient air flows into the oral flow passage2016 of the respiration sensor during inspiration.

In some embodiments, as illustrated in FIG. 17, a cross-sectional areaof the oral shroud 2017 forms an hourglass shape. For example, across-sectional area of the oral shroud 2017 can taper from the oralinlet 2036 toward the oral thermistor 400-3, positioned between the oralinlet 2036 and the oral outlet 2038, and can taper away from the oralthermistor 400-3 toward the oral outlet 2038. In some embodiments, asillustrated in FIG. 18, the cross-sectional area of the oral shroud 2017can taper from the oral inlet 2036 toward the oral outlet 2038. Thecross-sectional area of the oral shroud 2017 can also taper from theoral outlet 2038 toward the oral inlet 2036.

In some aspects, the oral shroud 2017 can have a cross-sectional profiletransverse to a flow through the oral shroud 2017. The cross-sectionalprofile of oral shroud 2017 can be any regular or irregular shape, suchas an oval, circle, square, or rectangle.

FIG. 18 illustrates a detail schematic view of the oral shroud 2017,including an oral flow guide 2034. The oral flow passage 2016 of theoral shroud 2017 collects the breathing gas flow ejected from apatient's mouth. The cross-sectional area of the oral shroud 2017 tapersfrom the oral inlet 2036 toward the oral thermistor 400-3, and from theoral thermistor 400-3 toward the oral outlet 2038. Alternatively, insome embodiments, the cross-sectional area of the oral shroud 2017 cantaper from the oral outlet 2038 to the oral inlet 2036.

The oral flow guide 2034 can direct at least portion of oral respirationflow 2032 moving through the oral flow passage 2016 of the oral shroud2017. An oral flow guide 2034 is disposed proximate an oral inlet 2036of the oral shroud 2017 and an oral flow guide 2034 is disposedproximate an oral outlet 2038 of the oral shroud 2017.

During expiration, the oral flow guide 2034 disposed proximate the oralinlet 2036 guides the breathing gas flow through the oral flow passage2016 and concentrates the breathing gas flow toward the oral thermistor400-3 while maintaining the breathing gas flow laminar as it passes theoral thermistors 400-3 to minimize turbulent noise. Similarly, duringinspiration, the oral flow guide 2034 disposed proximate the oral outlet2038 guides the ambient air flow through the oral flow passage 2016 ofthe respiration sensor and concentrates the ambient air flow toward theoral thermistor 400-3 while maintaining the ambient air flow laminar asit passes the oral thermistor 400-3 to minimize turbulent noise.

The oral flow guide 2034 extends from the oral shroud 2017 within theoral flow passage 2016. The oral flow guide 2034 can extend radiallyinward from an inner surface of the oral shroud 2017. The oral flowguide 2034 can extend across a portion of the oral flow passage 2016, oracross the oral flow passage 2016 to engage against an opposite innersurface of the oral shroud 2017. In some embodiments, the oral flowguide 2034 can extend between the oral inlet 2036 and the oral outlet2038. The oral flow guide 2034 can comprise a surface that is any of aplanar, a convex, and a concave surface. In some embodiments, the oralflow guide 2034 is arranged horizontally. In some embodiments, an oralflow guide 2034 is arranged horizontally and another oral flow guide isarranged vertically.

FIG. 19 illustrates a schematic view of the oral flow passage 2016including an entry angle ε that can create gas flow turbulence 2040. Ifthe entry angle ε is too high, the oral shroud 2017 will create theturbulence 2040 in both directions during inspiration and expiration.FIG. 20 illustrates turbulent noise flow turbulence 2040 duringexpiration, which is represented by expiration curve 2042 of themeasured electrical signal from a thermistor, such as thermistors 400-1,400-2, 400-3, 500-1, 500-2.

In some embodiments, a cross-sectional area of the oral inlet 2036mimics a dimension of a patient's open mouth during sleep, but is muchless than a fully open mouth and less than a diameter of a patient'sforefinger. In some embodiments, the oral inlet 2036 is elliptical inthe vertical direction. In such embodiments, the height of theelliptical oral inlet 2036 is approximately 9 mm and the width is lessthan the height, such as approximately 5 mm. In some embodiments, theoral outlet 2038 is elliptical. In some embodiments, the oral outlet2038 is circular. In some embodiments where the both the oral inlet 2036and the oral outlet 2038 are elliptical, the entry angle ε is relativelysmall, such that less turbulence is generated, but the gas flow is lessconcentrated towards the oral thermistor 400-3. In some embodiments, theoral outlet 2038 is approximately 5 mm.

Analysis of entry angle and turbulence generation in the flow cavity,can also be used with reference to the nasal flow passages 301, 2018.FIGS. 21A and 21B illustrate schematic views of possible nasalexpiration flow angles, which can be used to determine the potential forturbulence 2040. For example, in a flow path to the side of the nose, anangle a determines a flow width W of the flow path and an angle βdetermines the direction of the flow path nose. The flow width W is thedistance between flow paths from both nostrils. A gas flow column(referred to herein as GFC) is gas flow directed away from the face andthe nose. For example, in a flow path directed away from the face andthe nose, an angle γ determines a width of the flow path and an angle δdetermines the direction of the flow path away from the face and thenose. An area CA defines the cross-sectional surface area of a nostril,which affects the average width of a GFC. In general, a smallercross-sectional surface area CA of the nostril generates a narroweraverage width of the GFC. Moreover, turbulence 2040 may be createdaround the thermistors 400-1, 400-2 by narrow (e.g., low angle a and lowcross-sectional surface area CA) breathing GFC that is far to the sideof the nose (e.g., high angle β).

III. Respiration Sensor Size and Adjustability

FIGS. 22A, 22B, 23, and 24, illustrate potential distances or dimensionsof a patient's facial features or structures, determination of potentialdimensions of the respiration sensor using the measured and averagepatient facial features, and average measurement results for variouspatient's facial features or structures.

FIGS. 22A and 22B illustrate potential distances or dimensions of apatient's facial features relative to an oral cavity 2016 having athermistor 400-3 when the respiration sensor is placed on or attached tothe patient. More particularly, the identified dimensions include thepatient's nose width A1, isthmus width B1, a distance C1 between thebottom of the nose and the upper lip, a distance D1 between the bottomof the nose and the oral passage (e.g. mouth), a distance E1 between thefront edge of the nasal passage and the upper lip, and a lip thicknessF1, e.g., the distance the lip protrudes outwardly relative to thephiltrum.

FIG. 23 illustrates a respiration sensor, such as, for example, therespiration sensor 100 a, 100 b, depicting dimensions of the respirationsensor, which can correspond to analysis of the measured features of thepatient as shown in FIGS. 22A and 22B. Accordingly, the measured facialfeatures identified in FIGS. 22A and 22B help facilitate the designdimensions of the respiration sensor 100 a, 100 b. A2 should be at leastA1, but preferably A2 is more than A1 to ensure capturing flow throughthe patient's nostrils. Similarly, B2 should be no more than B1, butpreferably B2 is less than B1 to ensure that B2 does not prevent ordisturb flow through the patient's nostrils.

The measured facial features shown in FIGS. 22A and 22B can be used toselect design dimensions of the respiration sensor shown in FIG. 23. Insome embodiments, measurements of particular patient can be used toselect design dimensions for the respiration sensor. In some examples,measurements of a group of patients, such as adults or children, can beused to select design dimensions for an adult respiration sensor or achild respiration sensor.

A measured facial feature can correspond to a design dimension of therespiration sensor. For example: a patient nose width A1 can be used toselect the width A2 of the respiration sensor; a patient isthmus widthB1 can be used to select the battery frame 2014 width B2; the distanceC1 between the bottom of the nose and the upper lip can be used toselect a height C2 of the respiration sensor housing 2001; the distanceD1 between the bottom of the nose and the oral passage can be used toselect a distance D2 between the top of the respiration sensor 100 a,100 b, adjacent the nasal inlet 2024 and the oral flow passage 2016,302; the distance E1 between the front edge of the nasal passage and theupper lip can be used to select a depth of the respiration sensor 100 a,100 b; and the lip thickness F1 can be used to select a depth F2 of theoral flow passage 302, 2016.

In some embodiments, the distance C2 of the respiration sensor 100 a,100 b is less than 20 mm, but preferably less than 15 mm. In someembodiments, the distance C2 of the respiration sensor 100 a, 100 b isapproximately 10 mm to accommodate different face structures. In someembodiments, width A2 of the respiration sensor 100 a, 100 b is morethan 25 mm, but preferably about 45 mm to adequately capture the gasflow of patients with large width A2. In some embodiments, the distanceD2 of the respiration sensor 100 a, 100 b is more than 5 mm, butpreferably more than 10 mm. In some embodiments, the distance D2 of therespiration sensor 100 a, 100 b is more than 15 mm to capture gas flowcoming out from the nostrils. In some embodiments, the cross-sectionalarea of the nasal flow passages 301, 2018 is greater than thecross-sectional area of the nostrils of a patient to capture breathinggas flow. In some embodiments, the battery frame 2014 includes adimension B2 corresponding to the isthmus width B1 and is preferablyless than 10 mm, but more preferably less than 5 mm. In someembodiments, the oral flow passage 2016 is located parallel to thebreathing gas flow directed from the mouth of the patient.

FIG. 24 illustrates a graph 2044 of average measurement results forvarious facial features of a sample of patients including the patient'snose width A1, the isthmus width B1, the distance C1 between the bottomof the nose and the upper lip, the distance D1 between the bottom of thenose and the oral passage (e.g. mouth), the distance E1 between thefront edge of the nasal passage and the upper lip, and the patient's lipheight F1. The graph 2044 illustrates the measurement results of a groupof 45 Caucasian people including women, men, and children between theages of 0 to 70 years old. The measured values influence the dimensionaldesigns of the respiration sensor 100 a, 100 b with respect to the noseand the mouth including the size of nasal passages and the location ofthe oral passage. It should be understood that measurements for patientsmay also be outside of the scope of the measured feature in this graph.

FIG. 25A illustrates a respiration sensor, such as, for example,respiration sensor 100 b that includes the distance D2 between the topof the respiration sensor 100 b, adjacent the nasal inlet 2024, and theoral flow passage 2016, 302. The distance D2 can be approximately equalto 15 mm for patients with a smaller distance D1. Such a respirationsensor can accommodate patients including a distance D1 in the range ofapproximately 10 mm to 25 mm. In some embodiments, the distance D1 isbetween approximately 5 mm to 50 mm.

FIG. 25B illustrates a respiration sensor, such as, for example, therespiration sensor 100 b that includes the distance D2 approximatelyequal to 33 mm for patients with a larger distance D1. Such arespiration sensor can accommodate patients including a distance D1 inthe range of approximately 24 mm to 40 mm. In some embodiments, thedistance D1 is between approximately 5 mm to 50 mm.

FIGS. 26 and 27 illustrate embodiments of features to attach therespiration sensor 100 a to a patient. The features to attach therespiration sensor 100 a can include any of a string, strap, or band,which can maintain a position of respiration sensor 100 a relative tothe patient's physiognomy. It should be understood that any of thefeatures to attach the respiration sensors 100 a or 100 b can includethe features to attach the respiration sensor to a patient.

A strap 150 a, shown in FIG. 26, can have ends that are attached to therespiration sensor 100 a to form a loop. The strap 150 a can have alength such that the respiration sensor 100 a is engaged against apatient's face when the device is worn by the patient. In someembodiments, an additional strap 150 b extends from any of the strap 150a or the respiration sensor 100 a. The additional strap 150 b canprovide additional support and tension to secure the device with thepatient. The strap 150 a and additional strap 150 b can be configuredsuch that a portion of the strap 150 a extends above a patient's ears,and a portion of the additional strap 150 b extends below a patient'sears.

FIG. 27 illustrates a respiration sensor 100 a having a placement band150 c. In some embodiments, the placement band 150 c comprises asemi-rigid framework that is configured to guide straps that overlay theplacement band 150 c and extend over preferred placement portions of apatient's face. In some embodiments, the placement band 150 c comprisesa flexible plastic material that is configured to substantially retainits shape during use. The flexible placement band 150 c can move, in afirst plane, towards or away from a patient's face. The placement band150 c can be moved or biased in the first plane to engage against thepatient's face and adapt to the shape of the patient's face. Theplacement band 150 c is less flexible relative to a second plane,transverse to the first plane, thereby preventing or resisting movementof the placement band 150 c along the patient's face or twisting of theband 150 c.

The placement band 150 a, 150 c can have a width that is approximately 5mm, but it can be wider or narrower. A wider band can reduce the surfacepressure on the face by the band. At least a portion of a surface of theband can be covered with a material that is soft and/or breathable. Forexample, a surface of the band configured to engage against the face orskin of the patient can comprise a cotton or similar material.

The shape of the band 150 c is configured to extend from the respirationsensor 100 a, below the cheek bones of the patient. The band 150 c cancurve from the area below the cheek bones of the patient toward thepatient's ears, forming a shape of an S-curve or similar.

The band 150 c can be coupled with one or more additional band and/orstrap. For example, the band 150 c can be coupled to any of straps 150 aand 150 b. When the straps 150 a, 150 b pull the band 150 c andrespiration sensor 100 a towards the patient's face, a force vector ofthe respiration sensor 100 a is approximately straight, towards the faceor upper lip of the patient. Accordingly, the band 150 c can decreasethe surface pressure against the patient's isthmus or another portionsof the patient's face or lip.

IV. Respiration Sensor Features for Monitoring and Analysis

FIG. 28 illustrates an exploded view of the respiration sensor 100 a,100 b for example, including a housing 2001, shroud 2012, andelectronics board 300, according to some embodiments.

The electronics board 300 includes the electronic components used in therespiration sensor 100 a, 100 b. The electronics board 300 can include abattery 1110 and sensors, such as a thermistor 400-1, 400-2, 400-3, anda capacitive plate. In some embodiments, the electronics board 300 ismade of, for example, glass-reinforced epoxy laminate material (e.g.,FR4 substrate) containing automatic machine placed components, commonlyused in automated mass series production to make the construction lowcost. The electronics board 300 can be coupled to a base plate or frame320. In some embodiments, the frame 320 includes plastics, whichcontains electrically conductive areas or conductors.

In some embodiments of the present disclosure, the battery 1110 can be adisposable or rechargeable battery. In some embodiments, the respirationsensor 100 a, 100 b is configured to be powered by solar energy. Forexample, the respiration sensor 100 a, 100 b can include a solar panelwhich can be coupled to a battery.

The shroud 2012 defines at least a portion of the nasal flow passagesand the oral flow passage of the sensor. In some embodiments, theelectronics board 300 is positioned between the frame 320 and the shroud2012. Any of the frame 320 and the shroud 2012 can include a cavity toprotect the electronics board 300 when the respiration sensor 100 a, 100b is assembled. The frame 320 and/or the shroud 2012 can be made ofelastic silicone, plastics, or similar material.

In some embodiments, an ambient air thermistor is positioned furtheraway from the breathing gas flow otherwise interfering ambient airmeasurement. In aspects of the present disclosure, the shroud 2012 caninclude a perforation 501 that enables ambient air to be in touch withthe ambient air thermistor through the shroud 2012 to get fast responsetime, but also to protect ambient air thermistor for example fromtouching with a finger or any unwanted air flow, such as airconditioning.

Referring to FIG. 29, a portion of the frame 320 can form a supportstructure for the thermistors 400-1, 400-2. The electronics board 300may include two perforations that enable two poles of the frame 320 topierce through the electronics board 300 to form the thermistor supportstructure. The poles locate and keep the board in place with amechanical locking mechanism. No screws or similar are needed. The polesalso contain electrical contacts on the tip of the poles wherethermistors 400-1, 400-2, which are sensitive to nasal breathing gasflow, are coupled. Electrically conductive connections 1012 on the sidesurfaces of poles further connect thermistors 400-1, 400-1 to theelectronics board 300 via electrical contacts on the top surface of theelectronics board 300 next to the poles. When the frame 320 is placedunder the electronics board 300, electrical contacts on the top surfaceof the frame 320 connect with adjacent electrical contacts on the bottomsurface of electronics board 300. Electrically conductive glue can beused to ensure electrical contact. In some embodiments, a thermistor400-3 sensitive to breathing gas flow through the mouth is located tothe tip of the electronics board 300. A bottom side of frame 320,adjacent to electronics board 300 contains an inset 303 to enablethermistor 400-3 to locate into the middle of the flow cavity.

Electrical signals from thermistors 400-1, 400-2, 400-3 proportional tocorresponding ambient, skin, nasal or oral temperature changes areconducted through the electrically conductive connections 1012 andconductors to central processing unit on the electronics board. Thecentral processing unit can convert the analog data into digital form,process and transmit the data wirelessly, for example, via an RFtransmitter, to a host where the data can be shown or displayed to acaregiver in a suitable form of numbers and/or waveforms.

FIG. 30 illustrates a detailed view of an electronics assembly 1200, forexample, any respiration sensor 100 a, 100 b which can include two nasalflow thermistors 400-1, 400-2 and one oral flow thermistor 400-3,according to some embodiments. Thermistors 400-1 and 400-2 areconfigured to measure breathing from nostrils. Thermistor 400-3 may beconfigured to measure breathing from the mouth. A thermistor 500-1 (seeFIG. 32) may also be included in electronics assembly 1200 to measureambient temperature.

Support structures 1230-1, 1230-2, 1230-3 contain electrical wires onboth sides of a strip between electrical connections at both ends of thestrips. The support structures can include first and second supportstructures 1230-1, 1230-2, which can support the nasal flow thermistors400-1, 400-2. Additionally, a third support structure 1230-3 can supportthe oral flow thermistor 400-3. In some embodiments, support structures1230-1, 1230-2, 1230-3 may include an electrically and thermallyinsulating material (e.g., FR4 substrate). Thermistors 400-1, 400-2,400-3 can be soldered to electrical connections in the first end of thestrips. Second ends of strips are placed into small holes in electronicsboard 300 and soldered to form electrical connections on the sides ofthe strip to corresponding electrical contacts on the board toelectrically connect thermistors 400-1, 400-2, 400-3 to sensorelectronics in the plane of the electronics board.

The cross-sectional areas of copper or similar traces within supportstructures 1230-1, 1230-2, 1230-3 are reduced to minimize thermal flowthrough the electrical conductors from the plane of board to thermistors400-1, 400-2, 400-3. To minimize the thermal mass of the thermistors400-1, 400-2, 400-3, the support structures 1230-1, 1230-2, 1230-3 canbe formed from a thermally non-conductive or insulating material. Theseoptimizations make thermistors 400-1, 400-2, 400-3 as sensitive aspossible to thermal changes caused by the breathing gas flowing past thethermistor during expiration or ambient gas flowing past the thermistorduring inspiration.

FIG. 31 illustrates a partial view 1300 of an electronics board 300 in,for example, any respiration sensor 100 a, 100 b including details of anasal flow thermistor 400-1, according to some embodiments. Supportstructure 1230-1 may include an FR4 substrate strip with thermistor400-1 placed on the tip of the strip. At the bottom of support structure1230-1, a soldered contact provides electrical contacts to thermistor400-1 on both sides of support structure 1230-1 (e.g., +/−terminals).

In some embodiments, the support structures 1230-1, 1230-2, can have aproximal portion coupled to the electronics board 300 and a distalportion transverse to a plane defined by the top of the electronicsboard 300. When the electronics board is positioned within the housing,the distal portion of the support structures 1230-1, 1230-2 can extendinto respective nasal flow passages. In some embodiments, the supportstructure 1230-3 can have a proximal portion coupled to the electronicsboard 300 and a distal portion that is normal with or substantiallyparallel to a plane defined by the top of the electronics board 300.

FIG. 32 illustrates a detailed view of a bottom portion of anelectronics board 300 of a respiration sensor 100 a, 100 b including athermistor 500-1 to measure skin temperature, and a capacitive plate orsensor 1401 to measure sensor location in the upper lip, according tosome embodiments. A respiration sensor including electronics board maybe turned on/off based on the signal. Additionally, in some embodiments,the electronics board 300 includes an accelerometer 1150.

FIG. 33 illustrates a detailed view of an electronics board 300 coupledwith a frame 320 and a battery 1110, according to some embodiments.Support structures 1130-1 and 1130-2 extend away from the electronicsboard, and include thermistors 400-1 and 400-2, respectively. Athermistor 500-1 sensitive to skin temperature may be located on thebottom side of the board as close to skin as possible. In someembodiments, the thermistor is placed close to one of the two ridgesabove the upper lip to ensure closest distance to skin. The frame 320most advantageously contains a perforation adjacent to thermistor thatenables better thermal contact to upper lip skin. Perforation can alsobe filled with thermally conductive material to increase conductivity toskin.

The electronics board 300 includes a battery contact tab 1111 thatextends toward the battery 1110. A portion of the spacer 2019 ispositioned between the battery contact tab 1111 and the battery 1110such that the contact tab 1111 is spaced apart from the battery 1110.When the spacer 2019 is coupled with the respiration sensor 100 b, thebattery 1110 the battery does not provide power to the respirationsensor 100 b.

In some embodiments, the board 300 includes an LED 2013, which can bevisible from an outer surface of the respiration sensor 100 b when therespiration sensor 100 b is assembled. In some embodiments, the board300 includes a microphone 2020. The microphone 2020 can detect ambientsounds or a patient speaking. The sound detected by the microphone 2020can be used to during processing of signals. For example, the sounddetected by the microphone 2020 can filtered out to reduce or removenoise in the signals from the other sensors.

In some embodiments, any respiration sensor 100 a, 100 b is anaffordable, disposable, wireless sensor configured to detect breath flowin real time. Accordingly, the sensor 100 a, 100 b includes a battery1110, which may provide several days (e.g., five days, or more) ofcontinuous, real time, fast response operation with a high signalquality. In some embodiments, the respiration sensor 100 a, 100 b isconfigured to measure a respiration rate (RR) and magnitude, and toprovide real time respiration waveforms, in digital and/or analog form.Furthermore, a processor circuit in the respiration sensor may beconfigured to determine trends and projections based on the real-timedata (e.g., via moving averages, Kalman filtering, and the like). Therespiration sensor 100 a, 100 b may also provide skin temperature, bodyposition, movement, fall detection (e.g., through an accelerometer1150), sensor placement, and the like.

V. Processing of Readings for Indications

FIG. 34 illustrates a block diagram 1410 of components, which areutilized on the electronics board 300 of the respiration sensor 100 a,100 b according to some embodiments. In such embodiments, theelectronics board 300 includes a temperature-to-voltage converter 1412,an analog-to-digital (AD) converter 1414, a central processing unit(CPU) 1416, and a communications module or radio transceiver 1418 forproviding a two-way data communication coupling to a network link thatis connected to a local network. Such communication may occur, forexample, through a radio-frequency transceiver. In addition, short-rangecommunication may occur, such as using a Bluetooth, Wi-Fi, or other suchtransceiver. In some embodiments, the CPU 1416 includes the Bluetoothlow energy processor 1160 (shown in FIG. 33).

In some embodiments, the temperature-to-voltage converter 1412 includesany of the thermistor 500-1, the thermistor 500-2, the thermistor 400-1,the thermistor 400-2, and the thermistor 400-3. In some embodiments, anyof the thermistors 400-1, 400-2, 400-3, 500-1, 500-2 are negativetemperature coefficient (NTC) type thermistors, such that thethermistor's electrical resistance decreases when the temperatureincreases. In some other embodiments, any of the thermistors arepositive temperature coefficient (PTC) type thermistors, such that thethermistor's electrical resistance increases when the temperatureincreases. The respiration sensor 100 a, 100 b can include anycombination of NTC type thermistors and PTC type thermistors. Thetemperature-to-voltage converter 1412 converts or transforms thetemperature resistance value detected at any of the thermistors to avoltage at Vout 1420. The AD converter 1414 then converts the Vout 1420into digital form, which is received by the CPU 1416 for furtherprocessing and calculations. In some embodiments, the CPU 1416 cantransmit the digital signal to the host monitor or other client device.The CPU 1416 can transmit the digital signal via the Bluetooth lowenergy processor 1160. In some other embodiments, the CPU 1416 transmitsthe digital signal to the communications module or radio transceiver1418 for wireless transmission to the host monitor or other clientdevice.

In addition to the respiration sensor 100 a, 100 b measuring ordetecting temperature differences between inspiratory and expiratory gasflows via the thermistors 400-1, 400-2, 400-3, the respiration sensor100 a, 100 b also measures or detects ambient air temperature via thethermistor 500-1 and conductive temperature from the patient's skin viathe thermistor 500-2.

In some instances, the thermistor 500-1 and the thermistor 500-2 includea wide operating temperature range and can be adjusted to include alowest and a highest temperature of operating range. The respirationsensor 100 a, 100 b is configured to measure or detect the electricalsignal voltages proportional to the ambient air temperature via thethermistor 500-1 and the skin temperature via the thermistor 500-2 andcompensate the signal offset, gain, and the peak to peak amplitudeerrors from the inspiratory and expiratory gas flow signal amplitude.

In some embodiments, any of the thermistors 400-1, 400-2, 400-3, 500-1,500-2 can measure any of an inspiratory gas flow, an expiratory gasflow, an ambient air temperature, and a conductive temperature. Forexample, when the respiration sensor 100 a, 100 b is turned on, but isnot yet placed on or attached to the patient's face, the thermistor400-1, 400-2, 400-3, 500-1, 500-2 detect ambient air temperature. Whenthe respiration sensor 100 a, 100 b is placed on or attached to thepatient's face, the thermistor 500-2 begins detecting the temperature ofskin on the patient's upper lip. Meanwhile, the thermistor 500-1 remainsdetecting the ambient air temperature and the thermistors 400-1, 400-2,400-3 begin detecting the temperature differences between theinspiratory and the expiratory gas flows (e.g., inspired ambient air andexpired warm gas coming out from the lungs).

During normal, stable ambient conditions, after the respiration sensor100 a, 100 b is placed on or attached to the patient's face, theelectrical voltage signals from the thermistor 500-2 (e.g., detectingambient air temperature) are stable and change slowly, whereas theelectrical voltage signal from at least one of the thermistors 400-1,400-2, 400-3 changes its amplitude relatively faster. In someembodiments where the thermistors are NTC type and thetemperature-to-voltage converter 1412 includes negative feedbackamplifiers, the electrical voltage signal changes between maximumvoltage proportional to ambient air temperature and minimum voltageproportional to temperature of exhaled warm, moister gas coming out ofthe patient's lungs.

In other embodiments where the thermistors 400-1, 400-2, 400-3, 500-1,500-2 are PTC type and the temperature-to-voltage converter 1412 includepositive feedback amplifiers, the electrical voltage signal changesbetween maximum voltage proportional to temperature of exhaled warm,moister gas coming out of the patient's lungs and minimum voltageproportional to ambient air temperature. In both NTC type and PTC typescenarios, the frequency of electrical signal may vary between 0 to 3 Hz(0-180 RR/min) depending on how fast the patient is inhaling andexhaling. Smaller patients tend to breathe relatively faster thanrelatively larger patients, such as adults.

FIG. 35 illustrates a block diagram 1436 of components, which areutilized on the electronics board 300 of the respiration sensor 100 a,100 b according to some embodiments. In such embodiments, theelectronics board 300 includes a temperature-to-voltage converter 1438,a filter 1440, an analog-to-digital (AD) converter 1442, a centralprocessing unit (CPU) 1444, and a communications module 1446 forproviding a two-way data communication coupling to a network link thatis connected to a local network. Such communication may occur, forexample, through a radio-frequency transceiver. In addition, short-rangecommunication may occur, such as using a Bluetooth, Wi-Fi, or other suchtransceiver. In some embodiments, the CPU 1444 includes the Bluetoothlow energy processor 1160 (shown in FIG. 33).

In some embodiments, the temperature-to-voltage converter 1438 includesany of the thermistors 400-1, 400-2, 400-3, 500-1, 500-2. In someembodiments, any of the thermistors are negative temperature coefficient(NTC) type thermistors, such that the thermistor's electrical resistancedecreases when the temperature increases. In other embodiments, any ofthe thermistors are positive temperature coefficient (PTC) typethermistors, such that the thermistor's electrical resistance increaseswhen the temperature increases. The respiration sensor 100 a, 100 b caninclude any combination of NTC type thermistors and PTC typethermistors. The temperature-to-voltage converter 1438 converts ortransforms the temperature resistance value detected at one of thethermistors 400-1, 400-2, 400-3, 500-1, 500-2 to a voltage at Vout 1448.In some embodiments, the temperature-to-voltage converter 1438 alsoincludes an amplifier 1451, which increases the voltage at Vout 1448 forincreased accuracy and resolution of the breathing gas flow signal.

The filter 1440 eliminates or subtracts any of the ambient air and theconducting skin temperature change from the breathing gas flow signal.The AD converter 1442 then converts the signal from the filter 1440 intodigital form, which is received by the CPU 1444 for further processingand calculations. In some embodiments, the CPU 1444 can transmit thedigital signal to the host monitor or other client device via theBluetooth low energy processor 1160. In some other embodiments, the CPU1444 transmits the digital signal to the communications module 1446 forwireless transmission to the host monitor or other client device. Insome embodiments, the filter 1440 is configured to subtract theelectrical signal detected by the thermistor 500-2 from the electricalsignal detected by the thermistor 500-1. In some embodiments, the filter1440 is configured to subtract the electrical signal detected by thethermistor 500-2 and the electrical signal detected by any of the nasalthermistor 400-1, the nasal thermistor 400-2, and the oral thermistor400-3 from the electrical signal detected by the thermistor 500-1.

FIG. 36 illustrates a respiration sensor detection state table 1458 fordetermining the respiration sensor placement and function. For example,an operation logic is derived from the electrical signals from thethermistor 500-1, the thermistor 500-2, and the thermistor 400-1, 400-2,400-3 to detect different states of the respiration sensor 100 a, 100 b.The different states of the respiration sensor 100 a, 100 b are utilizedto identify sensor placement with respect to the patient and function ofthe sensor for monitoring and notifying of these states. The respirationsensor 100 a, 100 b is capable of identifying, for example, early signsof respiratory depression, spasms, obstructions, and other symptoms, andnotifying of these identifications. In addition to notifying of suchidentifications, the respiration sensor 100 a, 100 b is also capable ofnotifying when an improper placement of the sensor is identified ordetected to alert a caregiver to check on the patient and make sure thatthe sensor is not obstructing the patient's airways or otherwisedisturbing the patient.

The respiration sensor 100 a, 100 b includes various detection statesincluding, but not limited to: a not-yet-placed state (Not Yet Placedstate 1460); a correctly-placed and measuring state (Correctly Placed &Measuring state 1462); a correctly-placed, but no breath state(Correctly Placed, No Breath state 1464); a loose device state (Loosestate 1466); a detached or no breath state (Detached or No Breath state1468), and an operating-temperature exceeded state (OperatingTemperature Exceeded state 1470).

In the Not Yet Placed state 1460, the respiration sensor 100 a, 100 b isnot yet placed on the patient. For example, when the respiration sensor100 a, 100 b is turned on, but not yet placed on or attached to theupper lip of the patient, the thermistor 500-2, the thermistor 500-1,and the thermistor 400-3 all detect a similar signal corresponding totemperature proportional to ambient temperature and the breath indicator1453 a (shown in FIG. 35) detects no breaths. Under these detectedconditions, the respiration sensor 100 a, 100 b determines that it is inthe Not Yet Placed state 1460 and will not transmit an alertnotification.

After the respiration sensor 100 a, 100 b is placed on or attached tothe upper lip of the patient, the thermistor 500-2 detects and adapts toa temperature close to skin temperature of the upper lip while thethermistor 500-1 remains detecting the ambient air temperature. In someembodiments, the temperature offset error in the thermistor 500-2, whichis caused by, for example, a mustache, may be ignored since thetemperature detection is enough to monitor the temperature change duringthe time it takes to detect or determine whether the sensor is in properplacement or not (e.g., not the absolute value). When the location ofthe sensor between the nasal and the oral passages of the patient isproper and the patient is breathing the thermistor 400-3 start to adaptto and detect the temperature of the sequentially changing gas flow(e.g., Breath). At this point, the breath indicator 1453 a determinesthat the thermistor 400-3 detected a breath. Under these conditions, therespiration sensor 100 a, 100 b determines that it is in the CorrectlyPlaced & Measuring state 1462 and will not transmit an alertnotification.

The respiration sensor 100 a, 100 b determines that it is in theCorrectly Placed, No Breath state 1464 when the thermistor 500-2 remainsdetecting and adapting to the skin temperature and the thermistor 500-1remains detecting the ambient air temperature, but the thermistor 400-3no longer sufficiently adapts or detects the gas flow temperature (e.g.,detects ambient air temperature instead) even though the breathindicator 1453 a detects breaths. In the Correctly Placed, No Breathstate 1464, the location of the respiration sensor 100 a, 100 b betweenthe nasal and/or oral cavities may be unsatisfactory and the gas flowthrough the sensor cavities may be insufficient and the respirationsensor 100 a, 100 b will transmit an alert notification indicating that“No Breath” is detected. It is also possible that, in the CorrectlyPlaced, No Breath state 1464, the patient is not breathing sufficientlyenough and needs immediate attention from clinical personnel.

The respiration sensor 100 a, 100 b determines that it is in the Loosestate 1466 when the thermistor 500-2 does not detect the skintemperature and detects, instead, a similar value as the thermistor500-1 (e.g., ambient air temperature) while the thermistor 500-1 remainsdetecting the ambient air temperature, the thermistor 400-3 detects thegas flow temperature, and the breath indicator 1453 a detects breaths.In the Loose state 1466, the respiration sensor 100 a, 100 b may bepositioned askew with respect to the upper lip of the patient, such thatbreathing gas flow is not properly detected or monitored, and therespiration sensor 100 a, 100 b will transmit an alert notificationindicating that a “Loose Sensor” is detected so that care personnel mayadjust the respiration sensor 100 a, 100 b with respect to the patient'supper lip.

The respiration sensor 100 a, 100 b determines that it is in theDetached or No Breath state 1468 when the thermistor 500-2, thethermistor 500-1, and the thermistor 400-3 all detect ambient airtemperature and the breath indicator 1453 a detects no breaths. In theDetached or No Breath state 1468, the respiration sensor 100 a, 100 b isdetached from the patient and it will transmit an alert notificationindicating “Sensor Detached.” In some embodiments, in the Detached or NoBreath state 1468, in addition to or alternatively, the respirationsensor 100 a, 100 b will transmit an alert notification indicating that“No Breath” is detected.

The respiration sensor 100 a, 100 b determines that it is in theOperating Temperature Exceeded state 1470 when temperature detected bythe thermistor 500-1 equals or exceeds the temperature detected by thethermistor 500-2. This means that the ambient temperature is too closeto the breathing gas temperature to give sufficient differentialtemperature readings, which is proportional to the respiration signalamplitude. Such a situation may occur when the patient is lying facedownward against a surface (e.g., bed or pillow). In the OperatingTemperature Exceeded state 1470, the respiration sensor 100 a, 100 bwill transmit an alert notification indicating an “Operating Error.”

In some embodiments, signals from the nasal thermistors 400-1, 400-2 arecompared to determine a state of the patient or the respiration sensor100 a, 100 b. The signal from the nasal thermistors 400-1, 400-2 can becompared relative to each other to determine if the respiration sensor100 a, 100 b is correctly placed on the patient. For example, a normalsignal from thermistor 400-1 or 400-2, and a low or non-existent signalfrom the other of thermistor 400-1 or 400-2, can indicate that therespiration sensor 100 a, 100 b is not positioned correctly relative tothe patient's nostrils.

The capacitive sensor 1401 can also be used to activate and/or turn onthe respiration sensor 100 b. In some embodiments, the processor can beset into a low power or sleep mode when the respiration sensor 100 b isin storage or not in use. When in the sleep mode, the respiration sensor100 b can process a measured value from the capacitive sensor 1401 andcompare the measured value to a previous value stored into the memory.The previous value stored into the memory can correspond to arespiration sensor 100 b that is not engaged against a patient's face.When the respiration sensor 100 b is placed on a patient's upper lip,the capacitive value measured by the capacitive sensor 1401 can change.The change of capacitive value can be caused by the capacitive sensor1401 engaged against the patient's lip or tissue, which can have adifferent permeability relative to another material such as thecapacitive sensor 1401 packaging or ambient air.

When a change in measured value from the capacitive sensor 1401 isdetected, the processor can change the sensor from the low power orsleep mode to a normal operating mode. In some embodiments, theprocessor can activate other electrical circuits on the electronicsboard when a change in measured value from the capacitive sensor 1401 isdetected. In some embodiments, when the respiration sensor 100 b isseparated from the face of a patient, and a measured value from thecapacitive sensor 1401 corresponds to a respiration sensor that is notengaged against a patient's face, the respiration sensor 100 b can turnoff. In some embodiments, the respiration sensor 100 b can turn off whenthe capacitive sensor 1401 detects a change back to the permeability of,for example, air and/or no breathes are detected. In some embodiments,the respiration sensor 100 b can wait for a predetermined safety timelimit, e.g., 5 minutes, and then turn off or enter a low power mode.

In some embodiments, the respiration sensor 100 a, 100 b can beginmeasurement automatically when the processor counts one or more breathsfrom any of the nasal and oral thermistors. For example, measurement canstart automatically when the processor counts three different successfulbreaths from the nasal and/or oral thermistors.

To determine the respiration sensor placement and function, theelectronics board 300 can include, for example, any of a Bluetooth lowenergy processor 1160, the temperature-to-voltage converter 1438, thefilter 1440, the AD converter 1442, the CPU 1444, the communicationsmodule 1446, and the breath indicator 1453 a stored in the memory 1453b.

The amplitude of the alternating electrical voltage signal from thethermistors 400-1, 400-2, 400-3, 500-1, 500-2 can be convertedproportional to a real temperature, for example into degrees of Celsius.In principle, when the patient breathes normally, the minimum amplitudeof electrical signal from the NTC type thermistors is proportional tothe maximum temperature of exhaled air and the maximum amplitude ofelectrical signal from the NTC type thermistors is proportional to theminimum temperature of inhaled ambient air. For the PTC typethermistors, the maximum amplitude of electrical signal is proportionalto the maximum temperature of exhaled air and the minimum amplitude ofelectrical signal is proportional to the minimum temperature of inhaledambient air. The conversion from electrical voltage signal totemperature is negative with NTC type thermistor, whereas the conversionfrom electrical voltage signal to temperature it is positive with PTCtype thermistor. Accordingly, both NTC and PTC type thermistors canprovide the same temperature value.

FIG. 37 illustrates the temperature of breathing (respiratory flows)during changes in ambient air temperature. The amplitude of thealternating breathing signal 1422 indicates a temperature differencebetween inhaled ambient air and exhaled gas from the lungs in degrees ofCelsius [C.°], and can be proportional to a strength of breathing orvolume and flow of breathing. The peak-to-peak amplitude of alternatingbreathing signal 1422, presented in degrees of Celsius [C.°], dependsmostly on the flow rate of gas and ambient air temperature 1424. As canbeen seen in FIG. 37 the peak-to-peak amplitude of the breathing signal1422 decreases when the ambient air temperature 1424 increases.

In some instances, if exhaled breathing gas flow and volume decreases,the measured signal amplitude decreases proportionally. Due to lower gasvolume there is less thermal energy, and due to lower gas flow speed,exhaled gas has more time to release thermal energy to surrounding airand sensor housing (e.g., housing 2001) before reaching the thermistor400-1, 400-2, 400-3. Additionally, the exhaled gas can have less thermalenergy to warm up the thermistor 400-1, 400-2, 400-3.

In some instances, if ambient air temperature decreases, the exhaled gasreleases even more energy due to higher energy difference between twogas mediums. On the other hand, the maximum breathing signal isproportional to ambient temperature, and is sensitive to ambient airtemperature changes, thus the peak-to-peak signal amplitude proportionalto sequentially changing inhaled and exhaled gas is also dependent onambient air temperature. In some instances, if ambient air temperatureincreases, the breathing signal amplitude between inspirations andexpirations decreases and, vice versa, the breathing signal amplitudebetween inspirations and expirations increase when ambient airtemperature decreases.

In some embodiments, energy in the form of heat from a patient's upperlip can be conducted through the respiration sensor housing tothermistors. In some instances, energy directed from or toward a gasflowing through the respiration sensor 100 a, 100 b can cause a similareffect as ambient air change. FIG. 38 illustrates breathing (respiratoryflows) during a change in thermal energy conducting temperature, forexample when the respiration sensor 100 a, 100 b is coupled to apatient's face. The sensor housing (e.g., housing 2001) that guides gasflow through the respiration sensor 100 a, 100 b is preferably made ofplastic, silicon, or similar material with low thermal coefficient tominimize its ability to absorb, store, and conduct thermal energy.However, the housing may conduct some thermal energy from patient'supper lip and elevate the sensor temperature, similar to ambienttemperature change. The change in temperate generates a small offset,represented by offset curves 1426, to the temperature signal 1428proportional to inhaled ambient air temperature decreasing the breathingsignal peak-to-peak amplitude. The thermistor 400-1, 400-2, 400-3 senseswhen thermal energy, stored during expiration, is released duringinspiration, and senses when thermal energy is released during theexpiration phase, thus decreasing the breathing signal peak-to-peakamplitude between inspired and expired phases. This offset, representedby the offset curves 1426, can dependent on any of the ambient airtemperature and the thermal coefficient of the sensor housing'smaterial, which is a constant based on laboratory measurement and can betaken into account. The thermal energy conducting from a patient's upperlip through the sensor housing is strongly dependent on the thermalconnection between the respiration sensor 100 a, 100 b and the patient'sface, which in turn is proportional to temperature and the electricalsignal from the thermistor 500-2.

When the respiration sensor has been placed on patient's face, each ofthe inlets to the nasal flow passage cavities can be separated from thecorresponding nasal outlet of the patient, and the inlet to the oralflow passage cavity can be separated from the corresponding oral outletof the patient (i.e., mouth). When the patient breathes, warm and moistbreathing gas flows through any of the nasal and oral flow passages.Warm and moister exhaled breathing gas releases thermal energy into theambient air if the ambient air temperature is lower than the exhaled airtemperature. The temperature of exhaled air decreases as shown in FIG.38 represented by the offset curves 1426, which decreases the breathingsignal amplitude. To get maximal breathing signal amplitude duringexhalation, the sensor housing or respiration sensor cavities arepositioned as close as possible to patient's nasal and oral passagecavities.

It can be important to have accurate breathing signal peak to peakamplitude proportional to patient's actual inspired and expiredbreathing efforts at any time and during any condition to be able todetect situations, such as, for example, opiates deteriorating patient'sbreathing, obstructions, bronchospasms, etc. Changes in ambient airtemperature and in conducting thermal energy may cause a decrease in thepeak-to-peak signal amplitude, which resembles a similar decrease, forexample, as when opiates deteriorate the patient's breathing. In orderto correctly identify or detect the cause of the decrease and to avoid amisidentification, such error signals can be compensated and eliminatedto prevent any false notifications of these error signals. Ambient airtemperature changes that decrease the breathing gas signal can becompensated and eliminated based on the temperature signal proportionalto the thermistor 500-1 sensitive to the ambient temperature.Compensation to the breathing gas signal is inversely proportional toincreases in the ambient air temperature, thus if the ambient airtemperature increases, then the gain of the breathing gas signal isincreased, and vice versa. Similarly, changes in skin temperature, whichis proportional to the conducting temperature through the sensor housing2001, also decrease the breathing gas signal and is compensated andeliminated based on the temperature signal proportional to thethermistor 500-2 sensitive to the skin temperature. Compensation to thebreathing gas signal is inversely proportional to increases in the skintemperature, thus if the skin temperature increases, then the gain ofthe breathing gas signal is increased, and vice versa.

In some embodiments, thermal transients can be eliminated and signalamplitude relative to ambient and thermal energy conducting temperaturescan be compensated to produce a respiratory flow signal. For example,after removing the thermal effects as discussed above with reference toFIG. 35, the breathing gas flow signal may be displayed at the hostmonitor or other client device. The accuracy and resolution of thebreathing gas flow signal is enhanced due to the elimination of thethermal transients and compensating the signal amplitude relative to theambient and conducting temperatures.

In some embodiments, a temperature is detected via the thermistor 500-2when the respiration sensor 100 a, 100 b is initially placed on apatient's upper lip. Small sensors placed on the patient's airways orclose to airways may block the airways if the sensor detaches or theattachment is loose. Some conventional approaches to mitigate thepossibility of the sensor from detaching or becoming loose are toincrease the size of the sensor and increase the adhesive area stuck tothe skin. Larger sized sensors, however, may be uncomfortable for apatient and the increase in adhesive may irritate the skin of thepatient, such that the patient may intentionally or unintentionallyremove or detach the sensor. Some other conventional approaches mayutilize a notification system when the sensor becomes detached. In suchapproaches, however, care personnel may experience “alarm fatigue”caused by false alarms. The disclosed respiration sensor 100 a, 100 bdetermines different suitable measurement parameters that are used tospecify different situations to generate appropriate notifications.

For example, when the respiration sensor 100 a, 100 b is turned on, butis not yet placed on or attached to the patient's face, the thermistor500-1, the thermistor 500-2, and the thermistor 400-3 detects ambientair temperature. Additionally, data for a breath indicator 1453 a can bestored in a memory 1453 b associated with the CPU 1444, and can indicatethat no breaths have been detected yet by the thermistors 400. While thememory 1453 b is illustrated to be included in the CPU 1444, it can be aseparate element. When the respiration sensor 100 a, 100 b is placed onthe patient's upper lip, the thermistor 500-2 comes into close contactwith or makes contact with the skin of the upper lip and beginsdetecting the skin temperature on the patient's upper lip as representedby a skin temperature curve. For example, at zero seconds, thethermistor 500-2 detects the ambient air of approximately 23° C. andwarms up after the respiration sensor 100 a, 100 b is placed on theupper lip of the patient, at approximately 8 seconds, to detect the skintemperature of approximately 35.5° C. at 55 seconds. Accordingly, whenthe respiration sensor 100 a, 100 b is removed or loosened from the skinon the patient's upper lip, the thermistor 500-2 adapts and beginsdetecting the ambient temperature.

In some embodiments, a temperature offset error may be induced to thethermistor 500-2 to compensate for any space between the thermistor500-2 and the patient's upper lip, such as a mustache or similar medium.As a result, the temperature detected by the thermistor 500-2 may differfrom the actual skin temperature. However, this compensation oradjustment may be tolerated as it may be important only to detect thetemperature change. For example, when the respiration sensor 100 a, 100b is placed on the patient's upper lip the thermistor 500-2 monitors ordetects the temperature trend over time until detection of removal ofthe respiration sensor 100 a, 100 b rather than measuring or detectingthe absolute skin temperature value.

In some embodiments, a temperature is detected via the thermistor 500-1during ambient temperature change. The thermistor 500-1 monitors ordetects the ambient temperature. For example, on an ambient temperaturecurve, the thermistor 500-1 detects an initial ambient temperature ofapproximately 23° C. at zero seconds and detects a new ambienttemperature of approximately 25° C. at 55 seconds when, for example, thepatient is transferred from an ambulance to a hospital environment.

In some embodiments, a temperature is detected via the thermistor 400-1,400-2, 400-3 during respiratory flows. The thermistor 400-1, 400-2,400-3 sequentially detects the temperature change of the breathing gasflow between exhaled breathing gas and inspired ambient air at aconstant ambient temperature of 25° C., as represented by a respirationtemperature curve. During expiration, exhaled humid and warm air flowsout from the nasal and/or the oral passages of the patient into thecavity, such as, for example, the nasal flow passages 301 and the oralflow passage 302, inside the sensor housing (e.g., housing 2001) causingtemperature of the thermistor 400-1, 400-2, 400-3 located inside thecavity to adapt to the exhaled gas flowing past the thermistor 400-1,400-2, 400-3. During inspiration, the patient inhales causing theambient air to flow through the cavity, such as, for example, the nasalflow passages 301 and the oral flow passage 302, inside the sensorhousing (e.g., housing 2001) towards the oral and/or nasal passages ofthe patient, at which point, the thermistor 400-1, 400-2, 400-3 adaptsback to the temperature of inhaled ambient air flowing past thethermistor 400. Thus, during expiration, the air flowing out from thelungs warms up the thermistor 400-1, 400-2, 400-3 and, duringinspiration, the ambient air cools down the thermistor 400-1, 400-2,400-3. The temperature difference between the inhaled ambient air andthe exhaled breathing gas decreases and approaches zero when thetemperature of the ambient air approaches the temperature of the exhaledbreathing gas. When the temperature of the inhaled ambient air exceedsthe temperature of the exhaled breathing gas the temperature differenceexceeds zero again, but changes its sign.

In some embodiments, continuous, real time measurements of respiratoryflows is determined. Accordingly, a curve indicates a respiration realtime waveform. Accordingly, the curve is a waveform including more thantwo breathing cycles, each cycle including an expiration phase (positiveamplitude) and an inspiration phase (negative amplitude). A respirationrate (RR) curve is a curve indicating a value of breaths per minute[bpm]. It can be calculated from respiration waveform curve according toequation RR=60 seconds/breathing cycle time [seconds]. Each respirationcycle has respiration magnitude that may be calculated from a differencebetween maximum amplitude of expiration and minimum amplitude ofinspiration (which is negative). In some embodiments, respirationmagnitude is proportional to a breathing flow rate. When a patientexhales, the warm, moist breathing gas from the lungs warm upthermistors 400-1, 400-2, 400-3 causing respiration waveform signalcurve to rise. During inspiration, ambient air cools down thermistors400-1, 400-2, 400-3 to a temperature close to the ambient airtemperature. Thus, the breathing cycle amplitude is proportional tobreathing gas flow rate or respiration magnitude, which is proportionalto a temperature change of thermistors caused by the cooling/warmingeffects of inspiratory and expiratory air flowing past the thermistors.In the particular case of curve, respiration magnitude is a value inpercentages indicating the breathing flow magnitude or rate, relative toa maximum breathing flow magnitude or a maximum rate for a particularpatient.

In some embodiments, a respiration rate over an extended period of timemay be monitored and fit to a curve. The curve may indicate arespiration magnitude, corresponding to the depth of breath, over anextended period of time. In some embodiments, curves may reflect bothrespiration rates and magnitude values calculated on a breath to breathbasis. In some embodiments, the curves may include average values toreduce large fluctuations in signals received from sensors. In someembodiments, respiration rate and variance may be desirable parametersfor detecting an upcoming heart stroke. In some embodiments, a breathingsignal variance may anticipate a stroke event approximately 6-8 hoursbefore the actual stroke. Similarly, overdose of opioids, or pain (e.g.,too little opioids) may cause changes in respiration variance that aredetectable in a respiration sensor, leading to quicker response andtreatment to mitigate or prevent the impending risk.

VI. Accelerometer Functions

Referring to FIG. 39, the respiration sensor 100 a, 100 b can provide,for example, body position, movement, and fall detection via theaccelerometer 1150 (shown in FIG. 33). The accelerometer 1150 measuresor detects acceleration, position, angular rotation and other parametersderived from electrical signals proportional to at least x-, y-, andz-axes directions of accelerometer 1150 and can detect the patient'sposition and movement, the patient's head position and movement,acceleration caused by movement of the respiration sensor 100, 100 b,100 c, and movement of patient's upper lip while talking or movement ofthe patient's heart. For example, the electrical signals from theaccelerometer 1150 can be sent or transmitted to a monitoring device,such as a host monitor or similar client device, via Bluetooth or othercommunication method to monitor mobile patients. In some embodiments,the accelerometer 1150 of the respiration sensor 100 a, 100 b is athree-dimensional accelerometer that measures acceleration and positionof at least x-, y-, and z-axes directions of the accelerometer 1150 aswell as rotation around at least these three axes.

As discussed above, the respiration sensor 100 a, 100 b detects movementand position to monitor, for example, that the respiration sensor 100 a,100 b has not fallen out of place with respect to the patient, that thepatient has not fallen, or that the orientation of the patient's head isnot obstructing the nasal and oral breathing gas flows (e.g., patient'sface is downward towards pillow or bed). For example, it is desirable toobtain information about how a patient's head is positioned when thepatient is lying in bed for determining the measurement of respiratorycycles from patients. When the patient is lying down on his/her backwith his/her face upwards the patient can, for example, turn his/herhead from left to right. In such a position, the patient can breathe ina manner that allows gas to flow freely through the nasal and/or oralcavities of the respiration sensor 100 a, 100 b. When the patient islying sideways, his/her head can turn upward or downward. In thissideways position, it possible for the patient's head to face sidewaysor upward, such that the patient can breathe in a manner that allows gasto flow freely through the nasal and/or oral cavities of the respirationsensor 100 a, 100 b. It is also possible, however, in this sidewaysposition, for the patient to turn his/her head downwardly toward the bedor a pillow, such that the gas does not flow freely or is obstructedthrough the nasal and/or oral cavities of the respiration sensor 100 a,100 b. This uneven gas flow or obstruction of gas flow can disturb themeasurement signal proportional to breathing or the patient's breathingmay be prevented or deteriorated. A similar result may occur when thepatient is laying on his/her stomach with his/her face downward into thebed or the pillow.

In such scenarios, the respiration sensor 100 a, 100 b may detect thedirection in which the patient's face is pointing via the accelerometer1150, which can also measure or detect the axial and/or angularposition. The position of the patient's head is determined or calculatedfrom the electrical signals in the x-, y-, and z-directions detected viathe accelerometer 1150. In some embodiments, the respiration sensor 100a, 100 b determines, via the signals proportional to the patient'sposition that are monitored by the accelerometer 1150, the position ofthe patient's head relative to the respiration sensor 100 a, 100 b. As aresult, the respiration sensor 100 a, 100 b, responsive to determiningthat the patient's head is in a position that inhibits or obstructs gasflow therethrough and/or causes the respiration sensor 100 a, 100 b, tofunction improperly, can transmit a notification to inform of suchpositioning to the host monitor or other client device via Bluetooth orother communication method.

FIG. 39 illustrates the respiration sensor 100 a, 100 b in use on apatient to identify or detect any of a seated position 1166, a movingposition 1168, and a fallen position 1170. In some embodiments, therespiration sensor 100 a, 100 b can identify or detect transitioning ofa patient between any of a seated position 1166, a moving position 1168,and a fallen position 1170. In some scenarios, the patient may be mobile(e.g., getting up from the bed to use the restroom) and it may bedesirable to monitor the patient's movement and position. For example,the patient may be recovering from a health issue and feel dizzy whengetting up from a stationary position, such that the patient may passout, fall down, or hurt himself/herself and require acute medicalattention and care. In some embodiments, the respiration sensor 100 a,100 b detects, via the signals proportional to the patient's positionthat are monitored by the accelerometer 1150, such situations andindicates or transmits a notification to inform or alert the hostmonitor or other client device via Bluetooth or other communicationmethod.

As an example, the patient may be in a seated position 1166 and stand upto an upright position 1168, such that the accelerometer 1150 detectsmovement of the patient's head via the electrical signals in the x-, y-,and z-directions. Further, as the patient moves or walks in the uprightposition 1168, the accelerometer 1150 detects each step or movement thepatient may make, such as when the patient gets out of bed to go to therestroom. Each step generates acceleration pulses that are detected bythe accelerometer 1150 via the electrical signals proportional toacceleration in the x-, y-, z-directions. If the patient happens to falldown to the fallen position 1170, the accelerometer 1150 detects a highacceleration value proportional to a falling down magnitude. With thepatient in the fallen position 1170 (e.g., lying on the floor) from theupright position 1168, the respiration sensor 100 a, 100 b determinesthat the patient has fallen down due to the accelerometer 1150 detectinga high acceleration value and determining the difference in thepatient's head position in the upright position 1168 and the fallenposition 1170. Responsive to the determination that the patient hasfallen down, the respiration sensor 100 a, 100 b, transmits anotification to inform or alert the host monitor or other client device,via Bluetooth or other communication method, that the patient has fallendown and may require immediate medical care.

Additional measurements can be made based on movement of a patient'supper lip when patient talks. Talking is vibration of air coming fromvocal cords and it may disturb the breathing gas flow measurement andthe calculation of respiration rate (RR). The movement of the upper lipmay be detected and indicate that the patient is talking. In someembodiments, movement of a patient's upper lip is detected by theaccelerometer 1150.

Additional measurement can be made based on movement of a patient'sheart. The measurements can be used to determine a heart rate of thepatient. FIG. 40 illustrates blood circulation through a heart 1172 asthe heart 1172 pumps blood through the body 1174, shown in FIG. 41.Blood from the systemic circulation enters the right atrium from thesuperior and inferior vena cava and passes to the right ventricle. Fromthe right ventricle, blood is pumped into the pulmonary circulation,through the lungs. Blood then returns to the left atrium, passes throughthe left ventricle and is pumped out through the aorta back to thesystemic circulation. Normally, with each heartbeat, the right ventriclepumps the same amount of blood into the lungs as the left ventriclepumps to the body. Arteries transport blood away from the heart. Theheart 1172 contracts at a resting rate close to 72 beats per minute.

Due to a specific orientation of the myocardial fibers, in a heartbeatcycle, the heart 1172 makes a wringing or twisting motion along itslong-axis. On the other hand, the heart's sequential contraction, whichallows superior and inferior blood to enter the right atrium andventricle as well as allows expansion to pump blood from the leftventricle and the atrium back to the systemic and pulmonary bloodcirculation, generate micro movement along heart's long-axis. This backand forth movement is slightly leaned to the right regarding the body'slongitudinal axis 1176, as illustrated in FIG. 41.

The heart's movement moves the whole body 1174 back and forth cyclicallyat the phase of a heartbeat close to the direction along body'slongitudinal axis 1176. This micro movement can be detected by theaccelerometer 1150 of the respiration sensor 100 a, 100 b. The mostsensitive direction for the accelerometer 1150 to detect would be thez-axis. In some embodiments, the accelerometer 1150 contains an angularmotion sensor or sensing elements, in addition or alternatively, suchthat it can be used to detect the heart's rotation along its long-axis,which also generates rotational force around body's longitudinal axis1176 at a phase of the heartbeat. Either or both the body's longitudinalmovement or rotational movement around the body's longitudinal axis 1176can be transformed to a heartbeat or heartbeats per minute value fromthe electrical signals of accelerometer. This heart rate (HR)information can be used together with the respiration rate (RR) and flowinformation, by the respiration sensor 110 a, 100 b, in early detectionand prevention of respiratory depression and other symptoms.

In some embodiments, the accelerometer 1150 can also detect rise andfall of a patient's chest or other thoracic movement. This informationcan be coupled with at least one of HR, RR, and other breath indicatorsto aid in early detection and prevention of respiratory distress andother illnesses.

VII. EtCO2 Surfaces

In some embodiments of the present disclosure, the respiration sensor,such as, for example, the respiration sensor 100 a, 100 b, can includeend-tidal CO2 (EtCO2) sensing features. The EtCO2 sensing features caninclude one or more EtCO2 sensitive surface. The one or more EtCO2sensitive surface can be positioned on an outer surface of the shroud2012 and on a surface of the oral shroud 2017. FIG. 42A shows a firstEtCO2 sensitive surface 402-1 positioned on an outer surface of theshroud 2012 and adjacent to the thermistor 400-1, a second EtCO2sensitive surface 402-2 positioned on an outer surface of the shroud2012 and adjacent to the thermistor 400-2, and a third EtCO2 sensitivesurface 402-3 positioned on an inner surface of the oral shroud 2017 andadjacent to the thermistor 400-3.

The EtCO2 sensitive surface can change color as a result of nasal and/ororal breath detection of CO2. For example, the EtCO2 sensitive surfacecan change color to indicate the presence of CO2. In some embodiments,the one or more EtCO2 sensitive surface is coupled with an electrode. Asnasal and/or or oral breath moves over the EtCO2 sensitive surface, achange in resistance can occur. The change in resistance is used todetermine the presence of CO2 or other breathing related conditions. Insome implementations, one or more EtCO2 sensitive surfaces may beincluded in an electronics board of a sensor, such as the electronicsboard 300, as shown in FIG. 42B.

Turning now to FIG. 42B, there is shown EtCO2 sensitive surfaces 404-1,404-2, 404-3 electrically coupled to the electronics board 300 via oneor more electrical contacts of the electronics board 300. In someimplementations, one or more EtCO2 sensitive surfaces 404-1, 404-2,404-3, collectively referred to as EtCO2 sensitive surfaces 404, may besprayed on a surface of one or more components of the electronics board300. For example, EtCO2 sensitive surface 404-1 may be sprayed onsupport structure 1230-1, EtCO2 sensitive surface 404-2 may be sprayedon support structure 1230-2, and EtCO2 sensitive surface 404-3 may besprayed on support structure 1230-3.

When sprayed on a surface of one or more components of the electronicsboard 300, the EtCO2 sensitive surface may be sprayed on to overlap acathode electrical contact and an anode electrical contact of thecomponent. For example, when EtCO2 sensitive surface 404-1 is sprayed onsupport structure 1230-1, the EtCO2 sensitive surface 404-1 may besprayed on to overlap a cathode electrical contact and an anodeelectrical contact of the support structure 1230-1. Similarly, when theEtCO2 sensitive surfaces 404-2, 404-3 are sprayed on support structures1230-2 and 1230-3, respectively, the EtCO2 sensitive surfaces 404-2 and404-3 overlap cathode electrical contact and an anode electrical contactof the support structures 1230-2 and 1230-3 respectively. In someimplementations, the EtCO2 sensitive surfaces 404, may be coupled to oneor more electrodes of the electronics board 300. For example, EtCO2sensitive surfaces 404-1 may be coupled to one or more electrodes of thesupport structure 1230-1, EtCO2 sensitive surfaces 404-2 may be coupledto one or more electrodes of the support structure 1230-2, and EtCO2sensitive surfaces 404-3 may be coupled to one or more electrodes of thesupport structure 1230-3.

Each EtCO2 sensitive surface 404 forms an electrochemical cell. Asdescribed above, as nasal and/or or oral breath moves over an EtCO2sensitive surface 404, a change in resistance can occur. The EtCO2sensitive surfaces 404 may be configured such that a change inresistance may be proportional to the content of CO2 molecules in thenasal and/or oral breath that moved over the EtCO2 sensitive surfaces404. The EtCO2 sensitive surfaces 404 may be coupled to an electricalcircuit and the change in resistance can be transformed to acorresponding voltage via the electrical circuit. The voltage value maybe transmitted to the central processing unit on the electronics board300. In some implementations, the central processing unit on theelectronics board 300 may be configured to determine the presence of CO2and/or other breathing related conditions based on the change inresistance and/or corresponding voltage. In some implementations, thechange in resistance and/or corresponding voltage may be transmitted toone or more electronic devices coupled to the sensors 100 a, 100 b, 100c, such as the monitoring devices described herein (e.g., hub 4, monitor6, and the like).

VIII. Interconnectivity

Referring to FIG. 43, a respiration monitoring system 1 is illustratedincluding a sensor 2, a hub 4, and a monitor 6. The sensor 2 may be thepreviously described sensor 10 or similarly configured as the previouslydescribed sensor 10. The sensor 2 may include one or more of the sensorsdescribed herein including, for example, sensor 100 a and/or sensor 100b. The sensor 2, hub 4, and monitor 6 can be in communication with eachother with wires or wirelessly. In some embodiments, any of a sensor 2,a hub 4, and a monitor 6 can be in communication with each other andwith a network 50. The network can include, for example, any of a localarea network (LAN), a wide area network (WAN), the Internet, a remote orcloud server, and the like. Further, network 50 can include, but is notlimited to a network topologies, including any of a bus network, a starnetwork, a ring network, a mesh network, a star-bus network, tree orhierarchical network, and the like. Although one sensor 2, hub 4, andmonitor 6 are shown, it should be understood that the respirationmonitoring system can include multiple sensors 2, hubs 4, and monitors6.

Some embodiments of the respiration monitoring system can include apatient inside a hospital, a patient at home (e.g., homecare), and otheroriginal equipment manufacturer (OEM) applications. Accordingly, in someembodiments OEM parameters can be added to monitoring system (i.e.,SpO2, Temp, NiBP, ECG etc.)

Communication between the sensor 2 and any of a hub 4 and a monitor 6can be established using low energy communication 8, such as Bluetooth.A hub near the respiration sensor, for example, attached to or near apatient, can enable longer respiration sensor operation time by usinglow energy communication 8. The low energy communication 8 can includeany of a wireless personal area network technology or Bluetooth. The hubcan also provide respiration sensor pairing with patient, which can helpsecure patient identification information. Further, the use of a hub 4with the sensor 2 can permit patient mobility and continuous monitoringthroughout the hospital.

A long distance communication 10 protocol (e.g., Wi-Fi, cellular orother communication) may provide data transfer between the hub 4 and amonitor 6. In some embodiments, data can transfer between the hub 4 anda monitor 6 through the network 50. In some embodiments, the sensor 2communicates with a hub in the form of a smartphone. The smartphonecommunicates to internet through Wi-Fi or cellular systems. Data can betransferred and saved into a cloud in real time. Patient data can beviewed in a different physical location in real time with a smartphone,a tablet, a laptop or desktop computer, a smart TV, and the like.

FIG. 44 illustrates a sensor 2, such as respiration sensor 110 a, 100 b,coupled to a patient's 20 head, and a hub 4 positioned adjacent to thepatient. The hub 4 provides a user interface to the clinician forbedside monitoring. The hub 4 can also provide connectivity andcommunication between the patient 20 and a network 50 of the hospital.

FIG. 45 illustrates a sensor 2, such as respiration sensor 110 a, 100 b,coupled to a patient's 20 head, and a hub 4, in the form of a smartphone14 connected via a band to the patient's 20 arm. The hub 4 provides auser interface to the clinician for bedside monitoring. The hub 4 canalso provide connectivity and communication between the patient 20 and anetwork 50 of the hospital. In some embodiments of the presentdisclosure, the smartphone 14 can be placed on a holder adjacent to thepatient. The holder can couple with the smartphone 14 to provide any ofa communication interface of charging of the smartphone 14.

The smartphone 14 may include a camera, which can be used for pairingwith the sensor 2; Bluetooth to communicate with a low power consumptionsensor 2; Wi-Fi to communicate with cloud & hospital network; a userinterface enabled for a patient and/or a caregiver; 4G, WCDMA, and GPS.In some embodiments, the smartphone 14 communication is disabled forin-hospital use, and enabled for out-of-hospital use. For example, inout-of-hospital use, when patient and user authentication may be lessreadily available, the smartphone 14 may perform a face recognitionalgorithm or other personal/visual/audible recognition algorithms topair the patient 20 and the respiration sensor 2, and authenticate thatthe pairing is correct and accurate. When any information is notauthenticated, smartphone 14 may issue an alert, sound an alarm, orcommunicate a warning to a nurse in the centralized system. In someembodiments, the smartphone 14 is configured to integrate with hospitalsystem to provide authentication of patient and/or user duringin-hospital use.

FIG. 46 illustrates an interaction between, for example, the sensor 2and the smartphone 14 in a respiration monitoring system, according tosome embodiments. As will be described further with reference to FIGS.51-55, the interaction can be used to pair the sensor 2 and the hub 4,and can be used to identify the patient with the sensor 2.

In a first step 1800A, a nurse or authorized healthcare personnel mayread data from the sensor 2 in a proximity mode (e.g., a sensoridentification value, such as a barcode and the like). In a second step1800B, the healthcare personnel may further read the patient's wristband12 to log in the respiratory data in the appropriate patient record. Ina third step 1800C, the healthcare personnel may securely place thesmartphone 4 in an arm belt 14 on the patient 20. After connection ofthe hub 4 with a network 50 or a centralized server, for example, thesensor 2 can send and/or receive, in real-time, continuous respiratorydata and other information to the network 50 or centralized server.

FIG. 47 illustrates a sensor 2, such as respiration sensor 100 a, 100 b,and a headdress 16 coupled to the head of a patient 20. The headdress 16provides an easy to wear, wireless monitoring structure for a mobilepatient. The headdress includes a hub 4, in the form of a pod 18 thatcan be coupled to the headdress 16 at a position adjacent the top of thepatient's head.

The headdress 16 can contain sensors attached to, integrated into or inconnection with headdress fabric. A sensor 2 (e.g., respiration sensor100 a, 100 b) can measure respiration rate and flow. The pod 18 caninclude a pod sensor 22 to measure any of skin temperature, ambienttemperature, or position, motion and acceleration of the patient.

A head sensor 24 can be configured to engage against the patient's headwhen the headdress is worn by the patient. In some embodiments, the headsensor 24 is positioned adjacent to the temple of the patient's headwhen the headdress is worn by the patient. In some embodiments, the headsensor 24 can extend across the patient's forehead. The head sensor canmeasure any of temperature, frontal EEG, frontal oxygen saturation, ormovement of the patient. In some examples, the head sensor 24 includeselectrodes positioned at different positions on the patient's head tomeasure full EEG.

An ear sensor 26 can be configured to engage against an ear lobe of thepatient when the headdress is worn by the patient. The ear sensor 26 canmeasure oxygen saturation. The sensor 2 and headdress sensors 22, 24, 26can transform physiological signals into electrical signals formeasuring physiological parameters. For example, respiration sensor 100a, 100 b, and/or other headdress sensors 22, 24, 26, can measure any ofrespiration rate (RR), breathing gas flow, nasal-SpO2, ear-SpO2,frontal-SpO2, pulse rate (PR), heart rate (HR), skin temperature,ambient temperature, core temperature, body position or movement, chestor thoracic motion, EtCO2, full-EEG, frontal EEG, or similar parameters.The sensors are located at suitable locations around the headdress,depending on the measured physical parameter, to enable optimizedmeasurement of that parameter.

Each sensor may contain a battery to electrically power up the sensorand each sensor may also contain a transceiver to communicate with ahost (e.g., network 50) or monitor further away. Preferably sensors areelectrically powered through wires 28 integrated into headdress 16,which connect the sensors with a battery located into one location onthe headdress 16. The sensors also communicate with the host through onetransceiver located in the pod 18. The data communication between thesensors and the transceiver can be via the wires 28 integrated intoheaddress. This simplifies the electronics and power managementinfrastructure, decreases radio frequency pollution, which improvescommunication quality, lowers the cost, weight and size, decreases thepower consumption and improves usability and patient comfort.

The sensors attached to headdress 16 only contain a minimum amount ofmechanics and electronics to simplify and minimize the sensorsinfrastructure. For example, to enable the measurement of aphysiological signal, only the parameter specific electronics to enableto transform the physiological signal of that specific parameter into anelectrical signal are located into each sensor. All the electronics thathave commonalities between the sensors can be combined in the pod 18,which can also include the battery, processing unit, transceiver andsimilar. This centralizing reduces complexity, makes size and weightsmaller, increase patient comfort and usability and also reduces thecost of the sensors.

Sensors located on fixed or certain places on the headdress 16 alsoincrease the usability and the quality of measurement as sensors locateand place optimally on patient's head regardless of patient's appearanceor differences between users. Simpler, easy to dress wearable systemalso increases the adoption of a complex multi-parameter system.

The pod 18 can be removed for reuse, and the headdress 16 and sensorstherein disposed. Disposability reduces cross contamination risk anddecreases care personnel's working time needed for otherwisedisinfecting products.

The pod 18 can include most of the electronics, radio transceiver,electrical power source such as a battery, processor etc. and software.The system hardware and mechanics are simplified by centralizing complexfunctions into a reusable pod, which also makes the system moreefficient, easy to clean to prevent cross contamination between patientsand low cost. Further, the top of the head is also one of the mostcomfortable places for the pod 18 when patient is lying, sitting ormoving, but it also ensures easy device access and alarm visibility tocare personnel.

Electrical signals from any of the headdress sensors 22, 24, 26 andrespiration sensor 2 can be transmitted from through the electricalwires 28 to the pod 18 where they are processed into suitable form to betransmitted wirelessly to the monitor. In some embodiments, the pod 18can communicate with any of the sensors 2, 22, 24, 26, headdress 16, andthe monitor via Low energy Bluetooth or similar communication method.Preferably the communication with the monitor is via WiFi, 3G, 4Gcommunication or similar. This ensures that data from a mobile patientcan be transferred to a monitor device and hospital from any placeinside or outside hospital.

To ensure data is not lost during communication interruption the pod 18can contain internal First in first out (FiFo) memory to record data fora time of interruption. The monitor shows the processed data in asuitable form, for example on the host's display in digits and waveformsand alarms the care personnel when needed.

The pod 18 can have electrical contacts on a surface, which areconfigured to engage against reciprocal electrical contacts 30 on asurface of a pod frame 32 coupled to the headdress 16. In someembodiments, the electrical contacts 30 in connection with the headdress16 are planar. When pod 18 is attached to pod frame 32 these electricalcontacts 30 connect electrical power and electrical data lines to enablepower and data transfer between the sensors 2, 22, 24, 26 and the pod 18through the electrical wires integrated into to headdress 16. Theattachment between the pod 18 and pod frame 32 may be mechanical slidingor pressing into rails or it may be magnetic or similar.

A battery inside the pod 18 can be rechargeable. When charging isneeded, the pod 18 can be separated from the pod frame 32 and coupled toa source of electricity. In some embodiments, the pod 18 can be placedon a wireless charging table or a docking station based on for exampleinductive charging.

The outer surfaces of pod 18 can be smooth to prevent injury, preventcatching on fabric, and permit easy cleaning and disinfecting. Poweron/off and similar functions are implemented with for example capacitivebuttons rather than mechanical buttons so that the user only touches themarked areas on the surfaces of pod 18. The pod 18 can have any of analarm light and an audible alarm. The alarm light or audible alarm canbe integrated inside the pod 18. The alarm light can become visiblethrough a partially transparent housing made of material such asplastic.

The headdress can include straps 34 a, 34 b that extend around at leasta portion of the patient's 20 head, as illustrated in FIG. 47. Theheaddress 16 can be configured so that, when the headdress 16 is worn bya patient 20, a first strap 34 a can extend over the top of thepatient's head, and a second strap 34 b can extend across the foreheadof the patient. The headdress 16 can include a fastener to permitattachment of the straps 34 a, 34 b to each other and to adjust theheaddress 16 to conform to a particular patient's head. The fastener caninclude any of a hook and loop fastener, button, snap, or adhesive. Insome embodiments, the at least a portion of the straps 34 a, 34 b orheaddress 16 is formed of an elastic material.

FIG. 48 illustrates an embodiment of a headdress 40, which extends alonga greater portion of the patient's 20 head relative to the headdress 16illustrated in FIG. 47. When worn by a patient 20, the headdress 40 canextend along any of the patient's head top, forehead, crown, and nape,as well as the upper lip. The additional area covered by the headdress40 distributes pressure against the patient 20 over a greater area,thereby reducing discomfort. Further, the additional area covered by theheaddress 40 can resist movement of the headdress 40 relative to thepatient's head. The headdress 40 can be used for adults and/or childrenas well as infants.

Referring to FIGS. 49 and 50, examples of monitors are illustrated. Themonitor can be any device or system where data is received from a hub 4or respiration sensor 2. FIG. 49 illustrates a monitor in the form of asmartphone 14. The smartphone 14 can be a patient's phone, a caregiver'sphone, or the phone of another person monitoring the patient. FIG. 50illustrates a monitor in the form of a central station 42. The centralstation 42 can be a television, computer station, display board, oranother display that can be observed by a person monitoring the patient.

The monitor can graphically display information regarding the patientand/or data received from any of the sensor 2 and hub 4. The displayedinformation can include a temperature value from at least one of twonasal flow passages, a temperature value from an oral flow passage, atemperature value of a patient's skin surface, and a temperature valueof a patient's environment. In some embodiments, the displayedinformation includes an identification of the patient and/or theirlocation (e.g., 1-1, 1-2, 2-1), SpO2 measurement, heart rate, andrespiration rate. Additionally, displayed information can include anindication of a patient's orientation or position. The patient'sorientation or position can be shown in text or as a symbol. Forexample, the text or symbol may represent whether the patient is lyingon the bed, is standing upright, is sitting up, or is in some otherposition.

IX. Pairing Process

As described above, the sensor device 2 may include one or more of thesensors described herein (including, for example, sensor 100 a and/orsensor 100 b), and at least a portion of sensor 2 may be positioned on apatient, such as on an upper lip of the patient. The sensor 2 mayinclude or work in connection with one or more processors, such as a CPUunit 1416, and together may be configured to initiate a pairing processwith a monitoring device, such as the hub 4, based on physiologicalparameters of the patient. Additional details of the pairing process isdescribed herein with reference to FIG. 51.

Turning now to FIG. 51, there is shown a flowchart illustrating apairing process of a sensor device and a monitoring device. For thepurpose of illustrating a clear example, components of the monitoringsystem 1, and components of the respiration sensors 100 a, 100 b,previously described herein, may be used to describe the pairing processof a sensor device and a monitoring device.

The method 5100 includes, by a sensor device, (such as the sensor device2), measuring a physiological parameter of a patient (block 5101). Thesensor 2 may initially be in a deep sleep mode or a low-power mode priorto measuring the physiological parameter of the patient; and, in someimplementations, the sensor 2 may be in the deep sleep mode or thelow-power mode while measuring the physiological parameter of thepatient. In a deep-sleep or low-power mode, the sensor 2 may beconfigured to operate using fewer associated processors (e.g., use onlyone of processors) than when the sensor 2 operates in a normal powermode or a high power mode. For example, in the deep-sleep or low-powermode, the sensor 2 may be configured to use only one of the associatedprocessors, and when the sensor 2 is in a normal mode or a high powermode, the sensor 2 may be configured to use all of the associatedprocessors. In the deep-sleep or low-power mode, the sensor 2 may beconfigured to only perform certain predetermined functions, such asmeasuring a physiological parameter of the patient and/or detectingwhether the sensor 2 or portion thereof is in contact with a portion ofthe patient's body, such as the upper lip. By operating using fewerassociated processors and/or performing only predetermined criticalfunctions, the sensor 2 decreases power consumption and increases itsbattery life.

The sensor 2 may remain in the deep sleep mode or low-power mode until athreshold condition related to the physiological parameter is satisfied.For example, the sensor 2 may be configured to measure the breath of thepatient (e.g., by use of any sensor and/or method described above) andconvert the breath to a digital signal and/or a numerical value. The oneor more processors associated with the sensor 2 may be configured tostore this physiological parameter data in a storage unit of the sensor2 or communicatively coupled to the sensor device 2. For example, theCPU unit 1416 may be configured to determine a respiration rate valueand/or flow rate value based on the measured breath and store therespiration rate and/or the flow rate of the patient in the storageunit. The breath may be measured at one or more nostrils or at the mouthof the patient as described by any of the mechanisms above.

The one or more processors associated with the sensor device 2, maydetermine if the measured physiological parameter satisfies a thresholdphysiological parameter value (block 5102). In some implementations, thethreshold physiological parameter value may be a certain value of therespiration rate and/or a flow rate. For example, if the physiologicalparameter is a breath of the patient, then the threshold physiologicalparameter value may be a certain level and/or a value of a respirationrate or a flow rate. In some implementations, the one or more processorsassociated with the sensor device 2 may be configured to determinewhether the threshold physiological parameter value is satisfied basedon whether a consecutive number of measurements of the physiologicalparameter satisfy a certain value.

In some implementations, the one or more processors associated with thesensor device 2 may be configured to determine if each of theconsecutive number of measurements of the physiological parameter is atleast a certain value. For example, if the measured physiologicalparameter is a breath of the patient, then the threshold physiologicalparameter may be a respiration rate and it may be specified that each ofthe consecutive number of measurements of the respiration rate be atleast a certain level. The one or more processors associated with thesensor device 2 may be configured to track a consecutive number ofmeasurements of the physiological parameter that satisfy a thresholdvalue of the physiological parameter via a counter. The one or moreprocessors associated with the sensor device 2 may be configured toreset the counter if one of the measurements of the physiologicalparameter does not satisfy the threshold value of the physiologicalparameter.

If the one or more processors associated with the sensor device 2determines that the measured physiological parameter value does notsatisfy the threshold physiological parameter value (‘NO’ at block5102), then the method 5100 continues to block 5101. If the one or moreprocessors and/or the sensor device 2 determine that the measuredphysiological parameter value satisfies the threshold physiologicalparameter value (‘YES’ at block 5103), then the method continues toblock 5103.

The one or more processors associated with the sensor device 2 may beconfigured to cause the sensor device 2 to enter an active mode (block5103). In the active mode, at least a majority of the modules of thesensor device 2 are powered-on, and the sensor device 2 may beconfigured to operate at a higher performance level than when the sensordevice 2 is operating in low-power mode or deep sleep mode. The sensordevice 2 may operate at a higher power level in the active mode thanwhen the sensor device 2 is in a deep sleep or low-power mode, and thesensor device 2 may be configured to operate using all or most of theprocessors associated with the sensor device 2 while the sensor device 2is in active mode. The one or more processors associated with the sensordevice 2 may automatically cause the sensor device 2 to enter the activemode in response to the measured physiological parameter valuesatisfying the threshold physiological parameter value. The one or moreprocessors associated with the sensor device 2 may be configured toautomatically broadcast a wireless advertisement signal (block 5104). Inresponse to the sensor device 2 entering the active mode, the one ormore processors associated with the sensor device 2 may be configured toautomatically broadcast the wireless advertisement signal. In someimplementations, the wireless advertisement signal may be a Bluetoothsignal.

The one or more processors associated with the sensor device 2 may beconfigured to receive a wireless request to perform a pairing processbetween with a monitoring device (block 5105), such as hub 4. The sensordevice 2 may receive the wireless request from the monitoring device inresponse to automatic broadcast of the wireless advertisement signal.The one or more processors associated with the sensor device 2 may beconfigured to automatically complete the pairing process with themonitoring device (block 5106). After the pairing process isautomatically completed, the one or more processors associated with thesensor device 2 may be configured to communicate with the monitoringdevice. In some implementations, the one or more processors associatedwith the sensor device 2 receives a patient identifier of a patientduring the pairing process. For example, the monitor device, hub 4, maytransmit the patient identifier of the patient to the sensor device 2after sending the wireless request to perform the pairing process withthe hub 4. In some implementations, the one or more processorsassociated with the sensor device 2 stores the patient identifier of thepatient in a storage unit associated with and/or operably coupled to thesensor device 2. In some implementations, prior to the initiation of thepairing process, the monitoring device, such as hub 4, may be configuredto capture the patient identifier of the patient. Additional details ofthe monitoring device capturing the patient identifier are describedbelow with reference to FIGS. 54 and 55.

In some implementations, the one or more processors associated with thesensor device 2 may be configured to determine and associate a colorwith the sensor device 2. The sensor device 2 may be configured todetermine the color after the sensor device 2 enters the active mode,and display the color via an electronic component of the sensor device 2that is configured to emit or display color or colored light. Examplesof such electronic components include, but are not limited to, lightemitting diodes (LED), and the like. In some implementations, the LEDmay be a multicolor LED connected to a circuit that selects one ofmultiple predetermined colors to be illuminated by the LED (e.g., byproviding a predetermined voltage to a pin of the LED corresponding to aparticular color). Additional details of the sensor device 2 determiningthe color is described herein with reference to FIG. 52.

In some implementations, the sensor device 2 may continue to remain indeep sleep mode until it detects skin and/or tissue of a patient. Insome implementations, one or more processors of the sensor device 2 areactivated when skin and/or tissue of the patient is detected. In someimplementations, the sensor device 2 may be configured to determinetemperature of skin of the patient, temperature of breathe, and thelike, when skin and/or tissue of the patient is detected. In someimplementations, when skin and/or tissue of the patient is detected, thesensor device 2 may determine if the temperature of the skin is near 37degrees Celsius, and in response, initiates detection of the thresholdnumber of breaths from the patient.

Turning now to FIG. 52, there is shown a process to determine a colorassociated with a sensor device, such as the sensor device 2. The method5200 includes, at a sensor device, such as the sensor device 2,determining a unique identifier associated with the sensor device by theone or more processors associated with the sensor device (block 5201).Each sensor device may be associated with a unique identifier and theunique identifier may be stored in a storage unit of the sensor device2. The one or more processors associated with the sensor device 2, suchas the CPU unit 1416, may be configured to determine the uniqueidentifier by retrieving the unique identifier stored in the storageunit of the sensor device 2.

In some implementations, the color associated with the unique identifiermay be determined based on a character of the unique identifier. In someimplementations, the color associated with the unique identifier may bedetermined based on one or more characters present at one or morepositions of the unique identifier. For example, the color may bedetermined based on a character present in the last position of theunique identifier. Similarly, the color may be determined based oncharacters present in the second and third positions of the uniqueidentifier. The one or more processors and/or sensor device 2 may beconfigured with a set of rules that specify different colors fordifferent characters that may be present in the desired positions of theunique identifier. For example, the set of rules may specify that if thecharacter in the last position of the unique identifier is an “A,” thenthe color is green. Similarly, the set of rules may specify that if thecharacters in the second and third positions of the unique identifier isa “1” and a “b” then the color is blue.

In some implementations, the set of rules may specify a color for eachpossible character that may be present in the desired positions of theunique identifier. The one or more processors associated with the sensordevice 2 may be configured to determine or retrieve the uniqueidentifier of the sensor device 2, determine the character present inthe desired position (e.g., last position) of the unique identifier, andbased on the set of rules and the character in the desired position,determine a color. For example, if the unique identifier of a sensordevice is “4cx1oD” and the desired positions for determining a color isthe last position, then the one or more processors associated with thesensor device 2, using the set of rules, may determine a color mapped toand/or associated with the character “D.” In some implementations, theone or more processors associated with the sensor device 2 may beconfigured to associate the determined color with the sensor device 2and store the association in a storage unit of the sensor device 2and/or a storage unit operably and communicatively coupled to the sensordevice 2.

The sensor device 2 may be configured to physically display the colorassociated with the unique identifier by illumination of the LED (block5203). The one or more processors associated with the sensor device 2may be configured to cause the color associated with the uniqueidentifier to be displayed on or via an electronic component of thesensor device 2 (not shown). The electronic component may be amulticolored LED configured to emit or display color or colored light Insome implementations, the multicolor LED may comprise a microcontrollerand multiple light emitting diodes that are configured to emit coloredlights, such as red, green, blue lights. The one or more processorsassociated with the sensor device 2 may be configured to cause a certaincolor to be displayed via the multicolor LED based on a combination ofthe different colored lights of the multicolor LED.

The one or more processors associated with the sensor device 2 may beconfigured to determine whether an identifier of the patient is receivedfrom a monitoring device (block 5204). As described above, themonitoring device, such as the hub 4, may be configured to transmit anidentifier of the patient together or concurrently with, or after,sending the wireless request to perform the pairing process. If the oneor more processors associated with the sensor device 2 determines thatthe identifier of the patient is not received (‘NO’ at block 5204), thenthe method proceeds back to block 5204. In some implementations, the oneor more processors associated with the sensor device 2 may be configuredto wait a predetermined amount of time prior to proceeding back to theblock 5204. For example, the one or more processors associated with thesensor device 2 may be configured to wait 10 seconds prior to proceedingto block 5204.

If the one or more processors associated with the sensor device 2determines that the identifier of the patient is received (‘YES’ atblock 5204), then the method proceeds to block 5205. The one or moreprocessors may be configured to associate the color with the identifierof the patient (block 5205). The one or more processors associated withthe sensor device 2 may be configured to store the association of thecolor with the received identifier of the patient in a storage unitassociated with the sensor device 2 and/or a storage unit operablycoupled to the sensor device 2. In doing so, the color is associatedwith the patient. The one or more processors associated with the sensordevice 2 may be configured to transmit information of the color to thepaired monitoring device (block 5206). In some implementations, the oneor more processors associated with the sensor device 2 may transmit amessage to the paired monitoring device indicating the color. In someimplementations, the one or more processors associated with the sensordevice 2 may include the information indicating that the color isassociated with the patient.

The one or more processors associated with the sensor device 2 may beconfigured to cause the color to be displayed on one or more userinterface (UI) components on the paired monitoring device (block 5207).Examples of UI components may be graphical user interface (GUI)components displayed on a display device of the monitoring device.Examples of the UI components may include, but are not limited to, oneor more GUI icons, boxes, labels, frames, background and the like. Insome implementations, a portion of the UI components may be displayed inthe color associated with the identifier of the patient. For example,one or more edges of a graphical icon, box, label, frame and/orbackground may be displayed in the color associated with the identifierof the patient. The one or more processors associated with the sensordevice 2 may be configured to transmit a message or a command to thepaired monitoring device, such as hub 4, to instruct the hub 4 todisplay the one or more UI components displayed on a display device ofthe hub 4 or associated with the hub 4 in a color associated with thepatient.

In some scenarios, the wireless connection between the sensor device andthe paired monitoring device may be lost. For example, the monitordevice may be lose power, may be damaged, and/or experience othertechnical issues that may cause the wireless connection to the sensordevice to be dropped or lost. The sensor device 2 may be configured todetect the loss of the wireless connection with the monitoring device,and the sensor device 2, in response to pairing with a new monitoringdevice, the sensor device 2 may be configured to associate the newmonitoring device with the patient via the association of patient andthe sensor device 2. Additional details of a sensor device, such assensor device 2, associating a new monitoring device with a patientassociated with a previously paired monitoring device is described withreference to FIG. 53.

Turning now to FIG. 53, there is shown a process to associate the newmonitoring device with the patient. The method 5300 includes, by asensor device, such as the sensor device 2, detecting loss of a wirelessconnection to the paired monitoring device, such as hub 4 (block 5301).The one or more processors associated with the sensor device 2, via thecommunication module of the sensor device 2, may be configured todetermine whether a wireless connection with a paired device, such asthe hub 4, is still connected. The one or more processors associatedwith the sensor device 2 may be configured to automatically broadcast awireless advertisement signal (block 5302). The one or more processorsassociated with the sensor device 2 may be configured to automaticallybroadcast a wireless advertisement signal in response detecting loss ofa wireless connection to the previously paired monitoring device, suchas the hub 4.

The one or more processors associated with the sensor device 2 may beconfigured to receive a wireless request to perform a pairing processwith a new monitoring device (block 5303). In some implementations, thenew monitoring device has not been previously associated with thepatient that is associated with the sensor device, the sensor device 2.The one or more processors associated with the sensor device 2 may beconfigured to automatically complete the pairing process with the newmonitoring device (block 5304). The one or more processors associatedwith the sensor device 2 may be configured to automatically complete thepairing process with the new monitoring device in response to thereceiving the wireless request to perform the pairing process with thenew monitoring device.

The one or more processors associated with the sensor device 2 may beconfigured to transmit the patient identifier to the new monitoringdevice (block 5305). As described above, the one or more processorsassociated with the sensor device 2 may store the received patientidentifier from the previously paired monitoring device in a storageunit of the sensor device 2 or a storage unit operably coupled to thesensor device 2. The one or more processors associated with the sensordevice 2 may be configured to retrieve the patient identifier from thestorage unit and transmit the patient identifier to the new monitoringdevice. In some implementations, the one or more processors associatedwith the sensor device 2 may be configured to determine a most recentlyassociated patient identifier with the sensor device 2 and transmit thatidentifier to the new monitoring device. The one or more processorsassociated with the sensor device 2 may be configured to causeassociation of the new monitoring device with the patient identifier(block 5306). In some implementations, the one or more processorsassociated with the sensor device 2 may be configured to transmit amessage or command to instruct the monitoring device to associate thepatient identifier transmitted to the new monitoring device with the newmonitoring device. In some implementations, the monitoring device may beplaced in a charging station, and connection with the charging stationcan be detected by the monitoring device (e.g., from a charging currentreceived from the charging station, and/or an accelerometer in themonitoring device. In some implementations, the monitoring device maygenerate alarms if not placed within a threshold amount of time. In someimplementations, the monitoring device may display a discharge button ona GUI and selection of the button sends a message to paired sensordevice 2 to turn itself off.

Turning now to FIG. 54, there is shown a pairing process with a sensordevice at a monitoring device. The method 5400, at a monitoring device,includes receiving a patient identifier of a patient (block 5401). Asdescribed above, in some implementations, a patient identifier of thepatient may be received by the monitoring device by scanning the patientidentifier. For example, the monitoring device, such as the hub 4, maybe configured with a scanning apparatus, such as a one-dimensional (1-D)scanner, two-dimensional (2-D) scanners, and the like. The monitoringdevice, hub 4, may be configured with an image capturing apparatus andmay be configured to receive a patient identifier of the patient via animage of the patient identifier captured by the image capturingapparatus of the monitoring device. The one or more processors of themonitoring device, such as the hub 4, may be configured to determine apatient identifier based on the image of the patient identifier. In someimplementations, the one or more processors of the monitoring device maybe configured to decode data encoded in barcodes, such as linearbarcodes, matrix barcodes, and the like. In some implementations, thepatient identifier may be encoded in barcodes, and the one or moreprocessors of the monitoring device may determine the patient identifierbased on an image of the barcode captured by the monitoring device. Anexample of a monitoring device, such as hub 4, receiving a patientidentifier is shown in FIG. 46.

The one or more processors of the monitoring device may be configured toautomatically initiate a pairing process responsive to receiving thepatient identifier (block 5402). As part of the pairing process, the oneor more processors of the monitoring device may initiate searching ofdevices configured to communicate via wireless communication. Forexample, the one or more processors of the monitoring device may beconfigured to search for devices configured to communicate via Bluetoothtechnology. In some implementations, the monitoring device, such as thehub 4, may be configured to operate in a low-power mode until themonitoring device receives a patient identifier of a patient. In someimplementations, the monitoring device may be configured to enter intoan active mode after receiving or determining the patient identifier.

The one or more processors of the monitoring device may be configured todetect wireless advertisement signal from a sensor device (block 5403),such as the sensor device 2. In some implementations, the wirelessadvertisement signal may indicate that the sensor device has received aphysiological parameter from the patient. The wireless advertisementsignal may indicate that the sensor device has received a thresholdphysiological parameter data. The wireless advertisement signal mayindicate that the sensor device is ready to be paired to the monitoringdevice. The one or more processors of the monitoring device may beconfigured to pair the monitoring device with the sensor device (block5404). The one or more processors of the monitoring device may beconfigured to pair the monitoring device with the sensor device inresponse to detecting the wireless advertisement signal from the sensordevice.

The one or more processors of the monitoring device may be configured toreceive a physiological parameter detected by the sensor device (block5405). As described above, examples of physiological parameter mayinclude, but are not limited to, respiration rate, flow rate, and thelike. The one or more processors of the monitoring device may beconfigured to cause displaying of the physiological parameter on adisplay device (block 5406). The one or more processors of themonitoring device may be configured to display the received data of thephysiological parameter in a GUI displayed on a display deviceassociated with the monitoring device. In some implementations, the oneor more processors of the monitoring device may be configured togenerate one or more visual representations of the data of the receivedphysiological parameter. Examples of the visual representations of thedata may include, but is not limited to, trendlines, and the like.

In some implementations, the monitoring device may be configured todetermine a color for one or more sensor devices paired with themonitoring device and modify one or more UI components displayed on themonitoring device based on the determined color. Additional details ofthe monitoring device determining a color are described herein withreference to FIG. 55. Turning now to FIG. 55, there is shown a processof determining a color for the paired sensor device by the monitoringdevice. The method 5500, at a monitoring device, includes determining acolor for the paired sensor device (block 5501). In someimplementations, the one or more processors of the monitoring device maybe configured to determine a list of colors that are in use orassociated with other sensor devices, and determines a color that isavailable for the paired sensor device based on the list of colors. Insome implementations, the monitoring device may be configured with anexception list of colors that cannot be associated with any sensordevices. For example, the colors on the exception list of colors may becolors that are used for emergency scenarios in medical facility. Theone or more processors may be configured to determine a color for thepaired sensor device based on the exception list of colors and thedetermined list of colors that are in use.

The one or more processors of the monitoring device may be configured toassociate the color with the paired sensor device (block 5502). The oneor more processors of the monitoring device may be configured to storethe association of the color with the paired sensor device in a storageunit of the monitoring device or a storage unit operably coupled to themonitoring device. The one or more processors of the monitoring devicemay be configured to associate the color with the patient (block 5503).In some implementations, the one or more processors of the monitoringdevice may be configured to store the association of the color with thepatient in a storage unit of a centrally located server. In someimplementations, the one or more processors of the monitoring device maybe configured to store the association of the color with the patient ina storage unit of the monitoring device.

The one or more processors of the monitoring device may be configured totransmit data indicating the color to the paired sensor device (block5504). In some implementations, the one or more processors of themonitoring device may be configured to transmit an instruction to thesensor device specifying that the sensor device display the transmittedcolor via an electronic component of the sensor device, such as an LED.The one or more processors of the monitoring device may be configured toautomatically modify one or more UI components to reflect the color(block 5505). As described above, examples of UI components may begraphical user interface (GUI) components displayed on a display deviceof the monitoring device. The UI components may include, but are notlimited to, one or more GUI icons, boxes, labels, frames, background andthe like. In some implementations, the one or more processors of themonitoring device may be configured to modify color of portion of the UIcomponents in the color transmitted to the sensor device. In someimplementations, one or more edges of a graphical icon, box, label,frame and/or background may be displayed in the color transmitted to thesensor device.

X. Speech Detection

Detection of a patient's speech during a monitoring session of a patientmay assist in identifying whether the patient is awake, lucid, and/orexperiencing any pain. Furthermore, detection of a patient's speechwhile a sensor device comprising breathing sensors is actively measuringrespiratory and/or flow rates of a patient may assist in improvingaccuracy of the measured breathing pattern data and provide a moreaccurate report to a user, such as a nurse or a doctor. The systems andmethods described herein provide for detection of a patient's speech andimprovement in the accuracy of the displayed breathing pattern data.Additional details of speech detection and improving accuracy ofbreathing pattern data are described herein with reference to FIG. 56.

Turning now to FIG. 56, there is shown a flow chart to detect speech ofa patient and adjust breathing pattern data. For the purpose ofillustrating a clear example, components of the monitoring system 1, andcomponents of the respiration sensors 100 a, 100 b, previously describedherein, may be used to describe the process of determining whether apatient is speaking and adjusting breathing pattern data.

The method 5600 includes receiving, by one or more processors of amonitoring device, data indicating breathing patterns from breathingsensors associated with left nostril, right nostril, and/or mouth ofpatient (block 5601). As described above, a sensor device, such assensor device 2, may include one or more breathing sensors, and in someimplementations, at least one breathing sensor may be configured to beproximal to a left nostril, a right nostril, and/or a mouth of thepatient when the sensor device is placed on the patient. As describedabove, the sensor device, such as the sensor device 2, may be configuredto send the breathing pattern data to the monitoring device Thebreathing sensor proximal to the left nostril may be associated with theleft nostril. Similarly, a breathing sensor proximal to the rightnostril may be associated with the right nostril, and a breathing sensorproximal to the mouth may be associated with the mouth. As describedherein, the term “data indicating breathing patterns” will be referredto as breathing pattern data.

The breathing pattern data from the breathing sensor associated with theleft nostril, right nostril, and mouth may represent respiration rates,and/or a flow rates from the left nostril, the right nostril, and mouth,respectively. In some implementations, this breathing pattern data mayinclude information that specifies that the data may be associated withthe left nostril, right nostril, and/or mouth. The one or moreprocessors of the monitoring device may be configured to store thereceived breathing pattern data of the left nostril, the right nostril,and/or mouth in a storage unit of and/or associated with the monitoringdevice.

The one or more processors of the monitoring device receiveaccelerometer data from the sensor device on the patient (block 5602).As described above, the sensor device, such as sensor device 2, may beconfigured to transmit accelerometer data from one or more accelerometersensors and/or gyroscope sensors of the sensor device to the pairedmonitoring device. The accelerometer data may indicate movement of thepatient and/or a portion of a patient. For example, the accelerometerdata may indicate movement of a lip, such as an upper lip, of thepatient. The sensor device may be configured to measure accelerometerdata while the breathing pattern data is measured. For example, theaccelerometer data may be measured simultaneously with the breathingpattern data. In some implementations, the one or more processors of themonitoring device may be configured to determine a current placementlocation of the sensor device on a patient based on the receivedbreathing pattern data. For example, the one or more processors may beconfigured to determine a current placement location of the sensordevice on a lip of the patient based on the received breathing patterndata.

The one or more processors of the monitoring device compare the receivedaccelerometer data with one or more predetermined motion patterns (block5603). The one or more predetermined motion patterns may be motionpatterns related to movement of a mouth, a lip (e.g. upper lip), and thelike of a human. In some implementations, data related to and/or modelsassociated with the one or more predetermined motion patterns may bestored in a storage unit associated with the monitoring device. Asdescribed above, the storage unit associated with the monitoring devicemay include, but are not limited to, one or more storage units includedin the monitoring device, one or more storage units located remotelyfrom the monitoring device and communicatively coupled with themonitoring device, and the like. In some implementations, the one ormore processors of the monitoring device may be configured to determinethe placement location of the sensor device on the patient. In someimplementations, the one or more processors may be configured toinitiate comparison of the received accelerometer data (or motion datadetermined based on accelerometer data) and the predetermined motiondata patterns in response to determining the placement location of thesensor device. The one or more processors may be configured to determinewhether the determined placement location is within a predetermineddistance of a lip of the patient.

The one or more processors of the monitoring device may be configured todetermine a motion pattern based on the accelerometer data. As describedabove, in some implementations, the one or more processors of themonitoring device may be configured to determine a frequency at whichthe motion pattern occurs. The one or processors of the monitoringdevice may be configured to determine a similarity level between thedetermined motion pattern and the one or more predetermined motionpatterns based on the comparison. In some implementations, thesimilarity level may be represented by a value, such as a numericalscore, alphanumerical score, a probability value, and the like. In someimplementations, the one or more processors may store the determinedsimilarity level in a storage unit associated with the monitoringdevice.

The one or more processors determine whether the patient is talkingbased on the comparison (block 5604). The one or more processors may beconfigured to compare the similarity level with a predeterminedthreshold similarity level to determine a likelihood that the patient istalking. The predetermined threshold similarity level may indicate aminimum level at which a motion pattern indicated by the accelerometerdata and the one or more predetermined motion patterns should match. Thepredetermined threshold similarity level may be represented in the sameformat as the determined similarity level. For example, if thesimilarity level is represented by a numerical value, then the thresholdsimilarity level may also be represented by a numerical value.

Based on the comparison, if the one or processors determine that thesimilarity level satisfies a predetermined threshold similarity level,then the one or more processors determine a high likelihood that thepatient is talking. If the one or more processors determine that thesimilarity level does not satisfy a predetermined threshold similaritylevel, then the one or more processors determine a low likelihood thatthe patient is talking. In some implementations, the one or moreprocessors of the monitoring device may receive audio data from amicrophone of the sensor device. The received audio data may be for thesame time period during which the accelerometer data was captured. Forexample, the sensor device may be configured to capture the audio dataand the accelerometer data simultaneously. The one or more processorsmay be configured to determine a decibel level of the received audiodata, and compare the decibel level with a threshold decibel level todetermine whether the decibel level of the audio data satisfies thethreshold decibel level. If the decibel level satisfies a thresholddecibel level, then the one or more processors may increase thelikelihood that a patient is talking. If the decibel level does notsatisfy a threshold decibel level, then the one or more processors maydecrease the likelihood that a patient is talking. In someimplementations, the one or more processors may first determiningwhether the decibel level satisfies the threshold decibel level, and ifthe decibel level satisfies the threshold decibel level, then the one ormore processors compare accelerometer data or the determined motionpattern with one or more predetermined motion patterns.

The one or more processors may be configured to compare the generatedlikelihood value that a patient is talking with a predeterminedthreshold likelihood value of a patient talking. The one or moreprocessors of the monitoring device may determine that the patient istalking if the generated likelihood value satisfies the predeterminedthreshold likelihood value of the patient talking. For example, ifpredetermined threshold likelihood of a patient talking is set at a 90%confidence level, then the one or more processors may determine that thepatient is talking if the generated likelihood value also indicates a90% confidence level that the patient is talking.

If the one or more processors determine that the patient is not talking(‘NO’ at block 5604), then the method 5600 proceeds to block 5601. Ifthe one or more processors determine that the patient is talking (‘YES’at block 5604), then the method 5600 proceeds to block 5605. The one ormore processors adjust the received breathing pattern data (block 5605).Prior to adjusting the breathing pattern data, the one or moreprocessors may be configured to determine whether the received breathingpattern data differs from a baseline breathing pattern data of thepatient by a threshold amount. The baseline breathing pattern data ofthe patient may be determined by the one or more processors of themonitoring device based on breathing pattern data received over multipleprevious periods of time. If the one or more processors determine thatthe received breathing pattern data does not differ from the baselinebreathing pattern data by threshold amount, then the one or moreprocessors may not adjust the received breathing pattern data in block5605, and the method proceeds to block 5606.

If the one or more processors determine that the received breathingpattern data differs from the baseline breathing pattern data by athreshold amount, then the one or more processors adjusts the receivedbreathing pattern data. As described above, the one or more processorsof the monitoring device may be configured determine a respiratoryand/or flow rate for the left nostril, right nostril, and/or mouth basedon the received breathing pattern data. The one or more processors maybe configured to adjust the received breathing pattern data by adjustingthe respiratory and/or flow rates of the left nostril, right nostril,and/or mouth by a predetermined amount. The predetermined amount may beselected based on one or more machine-learned models that were trainedto determine an effect on respiratory and/or flow rates of patients whentalking. In some implementations, the one or more processors may beconfigured to adjust the breathing pattern data by decreasing thedetermined respiratory and/or flow rates. For example the breathingpattern data may be decreased to reduce the difference between thedetermined respiratory and/or flow rate data and threshold respiratoryand/or flow rate data. In some implementations, if the patient is nottalking and the breathing pattern data cannot be measured correctly,then the one or more processors may generate alarm for sleep apneacondition.

The one or more processors display the adjusted breathing pattern data(block 5606). The one or more processors may be configured to displaythe adjusted breathing pattern data by causing the adjusted breathingpattern data to be displayed on a display device associated with themonitoring device. A display device included with the monitoring deviceand/or communicatively coupled to the monitoring device may be referredto herein as associated with the monitoring device.

While the above describes one or more processors of the monitoringdevice performing the process of detecting speech and adjustingbreathing pattern data, one skilled in the art should recognize that oneor more processors of the sensor device 2 may be configured to performthe process of detecting speech and adjusting breathing pattern data inaccordance with the process described in FIG. 56.

XI. Monitoring Device

As described above, a monitoring device, such as a hub 4, may beconfigured to receive physiological parameter data from a sensor deviceand display information and/or data related to the receivedphysiological parameter data on a display device of and/or associatedwith the monitoring device. Based on the received physiologicalparameter data, the monitoring device 4 may be configured to determinewhether the patient is at risk of experiencing certain physiologicaland/or medical conditions, such as sleep apnea, physical pain, nasalcavity conditions, and the like, generate alerts based on the determinedphysiological conditions, and/or provide alerts to one or more users,such as a nurse, a doctor, other clinicians, friends, and/or familymembers of a patient. The monitoring device may be configured todetermine a position of the sensor device on a face of a patient basedon the physiological parameter data. The position may be a location onthe face relative to a facial feature such as the nose, mouth/lips, orneck of the patient. The monitoring device may be configured todetermine whether a sensor device is properly positioned on the patientbased on the position of the sensor device.

Furthermore, the monitoring device 4 may be configured to receivelocation and/or movement data of the patient, e.g., from the sensordevice 2. The location data may include, but is not limited to, datafrom one or more wireless transmitter devices configured to transmittheir identifiers, such as beacon devices, and the like. The monitoringdevice may also be configured to receive movement data of the patient,e.g., from the sensor device 2. Examples of movement data of a patientinclude, but are not limited to, data from one or more accelerometersensors and/or gyroscope sensors on and/or associated with a patient(e.g., embedded in sensor device 2). The monitoring device 4 may beconfigured to determine medical conditions based on the movement data ofthe patient. For example, the monitoring device 4 may identify sleepapnea based on the movement data of the patient. The monitoring device 4may be configured to modify and/or update user interfaces based onlocation of the monitoring device 4. Additional details of monitoring apatient are described herein with reference to FIGS. 57-62.

Turning now to FIG. 57, there is shown a process to determine a positionof a sensor device on a patient. For the purpose of illustrating anexample, components of the monitoring system 1, and components of therespiration sensors 100 a, 100 b, previously described herein, may beused to describe the process of determining a position of a sensordevice on a patient. In some implementations, a monitoring device 4 mayinclude a memory storage unit. In some implementations, a monitoringdevice may be communicatively coupled with a remotely located storageunit (e.g., a cloud-based storage unit). One or more processors of themonitoring device may be configured to store data in any storage unitassociated with the monitoring device.

The method 5700 includes, by a monitoring device 4 receiving motion data(including, e.g., accelerometer data) from a sensor device on a patient(block 5701). As described above, the sensor device, such as sensordevice 2, may be configured to transmit motion data measured by one ormore accelerometer sensors and/or gyroscope sensors of the sensor deviceto the paired monitoring device. The motion data may indicate movementof the patient. For example, the motion data may indicate the patientmoving their head. The one or more processors of the monitoring devicereceive data indicating breathing patterns of a left nostril of thepatient from the sensor device on the patient (block 5702). As describedabove, a sensor device, such as sensor device 2, may include one or morebreathing sensors, and in some implementations, at least one breathingsensor may be configured to be positioned proximal to a left nostril ofthe patient when the sensor device is placed on the patient. Thebreathing sensor proximal to the left nostril may be programmaticallyassociated with the left nostril (e.g., via coded instructions). Asdescribed herein, the term “data indicating breathing patterns” will bereferred to herein as breathing pattern data. The breathing pattern datafrom the breathing sensor associated with the left nostril may representa respiration rate, and/or a flow rate from the left nostril, and, insome implementations, may include information that specifies that thisbreathing pattern data is associated with the left nostril (e.g., anidentification of the left nostril). The one or more processors of themonitoring device may be configured to store the received breathingpattern data of the left nostril in a memory storage unit associatedwith the monitoring device.

According to various aspects, one or more processors of the monitoringdevice receive data indicating breathing patterns of a right nostril ofthe patient from the sensor device on the patient (block 5703). Similarto the breathing sensor associated with the left nostril, a breathingsensor positioned proximal to the right nostril may be programmaticallyassociated with the right nostril. The breathing pattern data from thebreathing sensor associated with the right nostril may represent arespiration rate, and/or a flow rate from the right nostril. In someimplementations, this breathing pattern data may include informationthat specifies that the data is associated with the right nostril (e.g.,an identification of the right nostril). The one or more processors ofthe monitoring device may be configured to store the received breathingpattern data of the right nostril in a storage unit of and/or associatedwith the monitoring device.

The one or more processors of the monitoring device receive dataindicating breathing patterns of a mouth of the patient from the sensordevice on the patient (block 5704). Similar to the breathing sensorsassociated with the left and right nostrils, the breathing pattern datafrom the breathing sensor associated with the mouth may represent arespiration rate, and/or a flow rate from the mouth, and may includeinformation that specifies that the data is associated with the mouth.The one or more processors of the monitoring device may be configured tostore the received breathing pattern data of the mouth in a memorystorage unit associated with the monitoring device.

The sensor device may transmit the breathing pattern data of the leftnostril, right nostril, and/or the mouth to the monitoring device 4 atperiodic intervals. In some implementations, the sensor device maytransmit the breathing pattern data in real time or near real time suchthat the breathing pattern data received by the monitoring devicerepresents the current respiration rate and/or flow rate of the patientin real time or near real time. As data is received, one or moreprocessors of the monitoring device may be configured to timestamp thebreathing pattern data, or otherwise associate the received breathingpattern data with an instance of time or a period of time. In someimplementations, the associated instance or period of time may representthe time at which the breathing pattern data is captured by the sensordevice. In some implementations, the associated instance or period oftime may represent the time at which the breathing pattern data isreceived by the monitoring device. The one or more processors may beconfigured to store in the memory storage unit the received breathingpattern data along with an indication of time (e.g., a timestamp) thatrepresents and/or specifies the associated instance or period of time.

The one or more processors of the monitoring device compare the receiveddata indicating breathing patterns with threshold breathing pattern data(block 5705). The monitoring device may be configured with a thresholdbreathing pattern data for each type of breathing pattern data. Forexample, a threshold breathing pattern data for a left nostril, athreshold breathing pattern data for a right nostril, and/or a thresholdbreathing pattern data for a mouth may be stored in a storage unitassociated with the monitoring device. The one or more processors of themonitoring device may be configured to compare the received breathingpattern data of the left nostril with threshold breathing pattern datafor the left nostril. Similarly, the one or more processors may beconfigured to compare the received breathing pattern data of the rightnostril and the mouth with threshold breathing pattern data of the rightnostril and the mouth, respectively.

In some implementations, the threshold breathing pattern data may bepredetermined and provided as an input to the monitoring device. In someimplementations, the monitoring device may determine the thresholdbreathing pattern data based on a profile of the patient, such as abiographical and/or physiological profile of the patient. For example,the monitoring device may be configured to determine an expectedrespiratory rate and/or a flow rate (e.g., for the left nostril, rightnostril, and/or mouth) based on a patient's age, weight, height, and thelike. In some implementations, the monitoring device may be configuredwith one or more machine learned modules that implement amachine-learned model trained to determine an expected respiratory rateand/or flow rate based on biological and/or physiological factorsrelated to the patient, such as age, weight, height, and the like. Basedon the comparison, the one or more processors of the monitoring devicemay be configured to calculate a difference between the receivedbreathing pattern data and the threshold breathing pattern data andstore the difference in the memory storage unit associated with themonitoring device. For example, the one or more processors may calculatea difference between the left nostril breathing pattern data and theleft nostril threshold breathing pattern data, and store the differencein a storage unit of the monitoring device. Similarly, the one or moreprocessors may calculate and store a difference between the rightnostril breathing pattern data and the right nostril threshold breathingpattern data, and the mouth breathing pattern data and the mouththreshold breathing pattern data.

Based on the comparison, the one or more processors of the monitoringdevice determine whether the sensor device is placed correctly on thepatient (block 5706). The one or more processors of the monitoringdevice may determine whether the calculated difference between thereceived breathing pattern data and the threshold breathing pattern datasatisfies a threshold difference. If the calculated difference satisfiesthe threshold difference, then the one or more processors may determinethat the sensor device is placed correctly on the patient. For example,if a threshold difference is a three percent difference from thethreshold breathing pattern data, then the one or more processors of themonitoring device determines that the sensor device is placed correctlyif the calculated difference for the left nostril, right nostril, andthe mouth are within three percent of corresponding threshold breathingpattern data. If the calculated difference does not satisfy thethreshold difference, then the one or more processors may determine thatthe sensor device is placed incorrectly on the patient.

In some implementations, the one or more processors of the monitoringdevice may be configured to identify a portion of the sensor that is notpositioned properly if a calculated difference is close to thresholddifference but does not satisfy the threshold difference. For example,if the calculated difference for a left nostril is close to thethreshold difference but does not satisfy the threshold difference, thenthe one or more processors may generate an alert indicating that thepositioning of the sensor device on the patient needs adjustment nearthe left nostril. Similarly, if the one or more processors determinethat the calculated difference for the right nostril is close to thethreshold difference but do not satisfy their respective thresholddifferences, then the one or more processors may generate an alertindicating that the position of the sensor device on the patient needsadjustment near the right nostril or the mouth.

If the one or more processors of the monitoring device determine thatthe sensor device is not placed correctly on the patient (‘NO’ at block5706), then the method 5700 proceeds to block 5709. The one or moreprocessors of the monitoring device generate alert (block 5709). Thealert may specify that the sensor device is not positioned properly onthe patient. In some implementations, the one or more processors mayspecify instructions in the generated alert to reposition the sensordevice to an appropriate position on the patient.

If the one or more processors of the monitoring device determine thatthe sensor device is places correctly on the patient (‘YES’ at block5706), then the method 5700 proceeds to block 5707. The one or moreprocessors of the monitoring device adjust the threshold breathingpattern data based on the received data indicating breathing patterns(block 5707). In some implementations, the one or more processors may beconfigured to adjust the threshold breathing pattern data based on astatistical measurement (e.g., a weighted average) of the thresholdbreathing pattern data and the received breathing pattern data. In someimplementations, the one or more processors may store the adjustedthreshold breathing pattern data in a storage unit of a monitoringdevice.

The one or more processors of the monitoring device may be configured to(e.g., using accelerometer data received from sensor device 2) identifya position in a three-dimensional coordinate space system as the currentposition of the sensor device on the patient (block 5708). The one ormore processors of the monitoring device may be configured to determinea set of coordinates in a three-dimensional (3D) coordinate space systemand identify the set of coordinates as the position of the sensor devicein the 3D coordinate space system. For example, the one or moreprocessors may identify a set of coordinates at a center of a coordinatespace system, such as coordinates 0, 0, 0, and identify the set ofcoordinates 0, 0, 0 as the position of the sensor device in this 3Dcoordinate system. According to various implementations, the coordinatespace may be mapped to the patient's face (or a default face for apatient). The default coordinates (e.g., 0, 0, 0) may be mapped to afacial feature, such as the nose, lips/mouth, chin, or neck of thepatient. The one or more processors may store this set of coordinates ina storage unit associated with the monitoring device as a position or afirst position of the sensor device. Using the received motion data, theone or more processors of the monitoring device may calculate an offsetfrom the first position. Based on the offset, the one or more processorsof the monitoring device may determine a second set of coordinates inthe 3D coordinate space system and identify the second set ofcoordinates as a new or a second position of the sensor device in the 3Dcoordinate space system. The one or more processors may store the secondset of coordinates in a storage unit of the monitoring device as anupdated position or a second position of the sensor device in the 3Dcoordinate space system.

The one or more processors of the monitoring device display a positionof the sensor device on the patient in a user interface (block 5709).The one or more processors of the monitoring device may be configured topresent a graphical user interface (GUI) on a display device, anddisplay the position of the sensor device in the GUI. The one orprocessors of the monitoring device display the sensor device in the GUIbased on the stored position of the sensor device in the 3D coordinatespace system described above. In some implementations, the one or moreprocessors may be configured to generate a virtual representation of apatient's face, head, and/or body and display the sensor device at anappropriate position on the patient's face, head, and/or body. Forexample, the one or more processors display the sensor device on anupper lip and below the nostrils of the patient's face. In someimplementations, the one or more processors may display the virtualrepresentation of a patient's face, head, and/or body with reference tothe 3D coordinate space system described above, and display the positionof the sensor device based on one or more of the stored positionsdescribed above. In some implementations, the monitoring device mayreceive data from a capacitive sensor and/or skin thermistor of sensordevice 2 and based on that data and respiration and accelerometer data,the monitoring device may detect position of the sensor device 2 on thepatient.

In some implementations, the one or more processors may be configured todetect a movement of sensor device based on received breathing data anddisplay the movement in real-time in a user interface. Additionaldetails of detecting the movement and displaying the movement inreal-time are described below with reference to FIG. 58.

Turning now to FIG. 58, there is shown a process to detect a movement ofthe sensor device on a patient and display the movement in real-time ina user interface. For the purpose of illustrating a clear example,components of the monitoring system 1, and components of the respirationsensors 100 a, 100 b, previously described herein, may be used todescribe the process of detecting a movement of the sensor device basedon breathing pattern data and displaying the movement.

The method 5800 includes determining, by a monitoring device, such asthe hub 4, a first position of the sensor device on a patient (block5801). As described above, the one or more processors of the monitoringdevice may store a position of the sensor device on the patient in astorage unit associated with the monitoring device. The one or moreprocessors of the monitoring device may determine the first position ofthe sensor device based on the position data stored in the storage unitassociated with the monitoring device. For example, the one or moreprocessors may retrieve the most recently stored position data anddetermine the first position of the sensor device as the most recentlystored position. As described above, the monitoring device may receivedata from the sensor device in real-time or near real-time, therefore,the determined first position may be the current position of the sensordevice on the patient.

The one or more processors of the monitoring device receive dataindicating breathing patterns from breathing sensors associated withleft nostril, right nostril, and mouth of the patient (block 5802). Asdescribed above, such data may be referred to herein as breathingpattern data. The one or more processors track changes in therespiratory and/or flow rates of the left nostril, right nostril, and/ormouth (block 5803). Based on the received breathing pattern data, theone or more processors may determine a respiratory rate and/or flow rateof the left nostril, right nostril, and the mouth of the patient for acurrent period of time. As described above, the one or more processorsmay be configured to store respiratory and/or flow rates for each periodof time in a storage unit associated with the monitoring device. The oneor more processors may compare each determined respiratory and/or flowrate with the respiratory and/or flow rates at previous periods of time.For example, the one or more processors may compare the respiratoryand/or flow rate of the left nostril with the respiratory and/or flowrates of the left nostril at previous periods of time. Similarly, theone or more processors may compare the respiratory and/or flow rate ofthe right nostril and/or the mouth with previously received respiratoryand/or flow rates of the right nostril and/or the mouth, respectively.Based on the comparison, the one or more processors may track changes inthe respective respiratory and/or flow rates.

The one or more processors of the monitoring device determine a secondposition of the sensor device on the patient based on the trackedchanges and the first position (block 5804). Based on the trackedchanges, the one or more processors may determine whether therespiratory and/or flow rates are increasing, decreasing, or areunchanged. The one or more processors may determine that the respiratoryand/or flow rates are increasing if the change in the rates are above athreshold amount, decreasing if the change in the rates are below athreshold amount, and unchanged if the change is within a thresholdamount. The one or more processors may determine whether the respiratoryand/or flow rates are increasing, decreasing, or are unchanged overmultiple time periods.

The one or more processors may be configured to compare the changes inthe respiratory and/or flow rates for the left nostril, right nostril,and/or mouth with each other to determine a direction of movement of thesensor device on the patient. For example, if the changes for bothnostrils (and, in some instances, the mouth) indicate a decrease in therespective respiratory and/or flow rates in a first time period, anddata for a first nostril (e.g., the right nostril) indicates an increasein a second subsequent time period, then the one or more processors maydetermine that the sensor device moved towards the side of the patientcorresponding to the opposing nostril (e.g., the left side of thepatient, or beyond the left nostril). Based on the direction ofmovement, the one or more processors may be configured to determine thesecond position. In some implementations, the one or more processors maybe configured to determine a second position by adjusting the firstposition in the 3D coordinated space system by a predetermined offsetamount in the direction of movement.

The one or more processors may display a movement of the sensor deviceon a user interface based on the first and the second positions of thesensor device (block 5805). The one or more processors may be configuredto generate a graphical movement of the sensor device from the firstposition to the second position, and display the movement on the userinterface (e.g. a GUI). As described above, the user interface maydisplay a face and the one or more processors may display the movementof the sensor device on the face.

Turning now to FIG. 59, there is shown a process to predict a likelihoodof the patient experiencing sleep apnea. For the purpose of illustratingan example, components of the monitoring system 1, and components of therespiration sensors 100 a, 100 b, previously described herein, may beused to describe the process of predicting a likelihood of the patientexperiencing sleep apnea.

The method 5900 includes receiving, by a monitoring device, motion datafrom a sensor device on a face of a patient (block 5901). One or moreprocessors of the monitoring device receive data indicating breathingpatterns from breathing sensors associated with left nostril, rightnostril, and/or mouth of the patient (block 5902). The one or moreprocessors determine a head motion of the patient based on the receivedmotion data (block 5903). Based on this data, the one or more processorsmay determine a pattern (e.g., up and down, side to side, and the like)of the head motion. The one or more processors may also be configured todetermine a frequency at which the head is moving in a certain pattern.For example, based on the motion data, if the determined pattern of thepatient's head motion is up and down, the one or more processors maydetermine a number of times per ten seconds that a head moves up anddown.

The motion data and the breathing data may be compared with one or morepredetermined sleep patterns to determine whether the patient is in anormal state of sleep or is experiencing distress. According to variousimplementations, at least one of the one or more predetermined sleeppatterns associated with an indication of sleep apnea. The one or morepredetermined sleep patterns may include a predetermined movementpattern of a patient's head relative to a fixed position during apredetermined period of time associated with a predetermined breathingpattern for the predetermined period of time. In some implementations,the movement pattern may correspond to a lip or mouth movement (insteadof, e.g., the entire head). An apnea score may be generated based on astrength of similarity between the predetermined movement pattern and acurrent movement pattern identified by the received motion data, and thepredetermined breathing pattern and a current breathing patternidentified by the received breathing data, for a period of timeequivalent to the predetermined period of time.

In this regard, the one or more processors compare the determined headmotion with the one or more predetermined motion patterns (block 5904).The one or more predetermined motion patterns may be patterns of a headmovement associated with sleep patterns. In some implementations, thepatterns of a head movement associated with sleep patterns may be headmovement patterns associated with sleep apnea. In some implementations,the one or more predetermined motion patterns may be motion patternsidentified using machine learned models that were trained using headmotion data of patients that suffered sleep apnea. The one or moreprocessors may be configured to generate a an indicator (e.g., a sleepapnea score) that represents how closely the determined head motionmatches one or more predetermined head motion patterns based on thecomparison of the determined head motion with the one or morepredetermined motion patterns.

The one or more processors predict a likelihood of the patientexperiencing sleep apnea based on the comparison and the receivedbreathing pattern data (block 5905). The one or more processors may beconfigured to determine whether the generated indicator satisfies athreshold match level. If the generated indicator does not satisfy thethreshold level, then the one or more processors may decrease alikelihood that the patient may experience sleep apnea. If the generatedindicator satisfies the threshold level, then the one or more processorsmay increase the likelihood that the patient may experience sleep apnea.The one or more processors may be configured to further adjust thelikelihood that the patient may experience sleep apnea based on thereceived breathing pattern data. In some implementations, the one ormore processors may be configured to identify any irregularities in thepatient's breathing, and determine whether any irregularities occur ator near the same time period as the patient's head motion. If anyirregularities in the patient's breathing occur at the same time as thepatient's head motion, then the one or more processors may increase thelikelihood that the patient may experience sleep apnea, and if theirregularities do not occur at or near the same time period as thepatient's head motion, then the one or more processors may decrease thelikelihood that the patient may experience sleep apnea.

The one or more processors of the monitoring device determine whetherthe predicted likelihood satisfies a threshold likelihood level (block5906). In some implementations, the predicted likelihood may be a valuethat indicates a probability that the patient may experience sleepapnea. In some implementations, the predicted likelihood may be theprobability that the patient may experience sleep apnea within athreshold amount of time from a current instance or period of time. Ifthe one or more processors of the monitoring device determine that thepredicted likelihood does not satisfy the threshold likelihood level(‘NO’ at block 5906), then the method 5900 proceeds to block 5901. Ifthe one or more processors determine that the predicted likelihoodsatisfies the threshold likelihood level (‘YES’ at block 5906), then themethod proceeds to block 5907. The one or more processors may generatean alert (block 5907). The one or more processors may cause the alertand/or an indication of the alert to be displayed on a display deviceassociated with the monitoring device. In some implementations, on adisplay device associated with the monitoring device, the one or moreprocessors may cause the alert or the indication of the alert to bedisplayed together with a graphical representation of the sensor device.In some implementations, the one or more processors may cause the alertto be transmitted to an identifier (e.g., email address, phone number,and the like) of a user, such as a nurse, a doctor, and the like.

In some implementations, the one or more processors may be configured tocompare the determined head motion of the patient with one or morepredetermined head motion patterns associated with pain. The one or moreprocessors may be configured to generate a pain indicator (e.g., a painscore) that indicates a likelihood that the patient is experiencing painbased on the comparison. For example, the one or more processors maygenerate a score based on how closely the determined head motion matchesone or more predetermined head motion patterns associated with pain. Theone or more processors may be configured to display a graphical elementindicating the likelihood that the patient is experiencing pain. Forexample, the one or more processors may cause the generated pain scoreto be displayed in a GUI on a display device associated with themonitoring device.

According to various implementations, the motion data and/or thebreathing data may be compared with one or more predetermined distresspatterns to determine whether the patient is in a normal state of sleepor is experiencing distress. In this regard, at least one of the one ormore predetermined motion patterns associated with an indication ofdistress. The one or more predetermined distress patterns may include apredetermined movement pattern of a patient's head relative to a fixedposition during a predetermined period of time associated with apredetermined breathing pattern for the predetermined period of time. Insome implementations, the movement pattern may correspond to a lip ormouth movement (instead of, e.g., the entire head). A distress or painscore may be generated based on a strength of similarity between thepredetermined movement pattern and a current movement pattern identifiedby the received motion data, and the predetermined breathing pattern anda current breathing pattern identified by the received breathing data,for a period of time equivalent to the predetermined period of time.

Turning now to FIG. 60, there is shown a process to determine whether apatient is complying with an instruction from a clinician. For thepurpose of illustrating a clear example, components of the monitoringsystem 1, and components of the respiration sensors 100 a, 100 b,previously described herein, may be used to describe the process ofdetermining whether a patient is complying with an instruction from aclinician.

The method 6000 includes receiving, by a monitoring device, data relatedto an instruction provided to a patient (block 6001). The data relatedto the instruction provided to the patient may be provided via an inputdevice associated with the monitoring device. For example, if theinstruction provided to the patient is not get out of the bed, then,using a touchscreen display of the monitoring device, the clinician mayprovide information about the instruction provided to the patient, andthe one or more processors may receive the instruction. The one or moreprocessors receive accelerometer data from a sensor device on thepatient (block 6002). The one or more processors determine a movement ofthe patient based on the accelerometer data (block 6003). The one ormore processors may be configured to determine a motion based on thereceived accelerometer data and compare the determined motion withpredetermined motion patterns that indicate a movement of a patient.Based on the comparison, the one or more processors may determine amovement (e.g., sitting up, standing up, walking, and the like) of thepatient.

The one or more processors determine whether the movement of the patientcomplies with the received instruction for the patient (block 6004). Forexample, if the received instruction is that the patient should liedown, and the determined movement indicates that the patient is sittingup, then the one or more processors determine that the movement of thepatient does not comply with the received instructions. If the one ormore processors determine that the movement of the patient complies withthe received instruction (‘YES’ at block 6004), then the method proceedsto block 6002. If the one or more processors determine that the movementof the patient does not comply with the received instruction (‘NO’ atblock 6004), then the method proceeds to block 6005. The one or moreprocessors generate an alert that the patient is not in compliance withthe instruction (block 6005). The one or more processors may cause thealert to be displayed on a display device associated with the monitoringdevice. In some implementations, the one or more processors may causethe alert to be transmitted to an identifier (e.g., email address, phonenumber, and the like) of a user, such as a nurse, a doctor, and thelike.

Turning now to FIG. 61, there is shown a process to detect nasal cavityconditions based on received breathing pattern data. For the purpose ofillustrating a clear example, components of the monitoring system 1, andcomponents of the respiration sensors 100 a, 100 b, previously describedherein, may be used to describe the process of detecting nasal cavityconditions based on received breathing pattern data.

The method 6100 includes receiving, by one or more processors of themonitoring device, data indicating breathing patterns from breathingsensors associated with left nostril, right nostril, and mouth of thepatient (block 6101). The one or more processors determine respiratoryrate and/or flow rate for left nostril, right nostril, and mouth basedon the received breathing pattern data (block 6102). The one or moreprocessors compare respiratory and/or flow rates of the left nostril andright nostril with the respiratory and/or flow rates of mouth of thepatient (block 6103). The one or more processors may be configured tocalculate a difference based on the comparison of the respiratory and/orflow rates. For example, the one or more processors may calculate adifference between respiratory and/or flow rates of left nostril andmouth of the patient, and calculate another difference betweenrespiratory and/or flow rates of right nostril and mouth of the patient.The one or more processors may be configured to store the calculateddifferences in a storage unit associated with the monitoring device.

The one or more processors determine whether the patient has anunhealthy nasal cavity condition based on the comparison (block 6104).The one or more processors determine the patient has an unhealthy nasalcavity condition if the respiratory and/or flow rate of mouth of thepatient is greater than the respiratory and/or flow rate left nostriland/or right nostril. In some implementations, the one or moreprocessors may be configured to compare the calculated and/or storeddifferences with predetermined threshold difference values associatedwith nasal cavity conditions. If the one or more processors determinethat a calculated difference satisfies a predetermined thresholddifference value, then the one or more processors may be configured todetermine that corresponding nasal cavity is not completely unblocked orhealthy.

For example, the one or more processors may compare the calculateddifference between the left nostril and mouth with a thresholddifference, and if the calculated difference satisfies the thresholddifference, then the one or more processors may determine that the nasalcavity of the left nostril is not completely unblocked or healthy.Similarly, if the one or more processors compare the calculateddifference between the right nostril and mouth with a thresholddifference, and if the calculated difference satisfies the thresholddifference, then the one or more processors may determine that the nasalcavity of the right nostril is not completely unblocked or healthy. Theone or more processors of the monitoring device generates an alertindicating one or more nasal cavities are not completely unblocked(block 6105). In some implementations, the one or more processors mayindicate each nasal cavity that is determined to not to be completelyunblocked in the alert. For example, if the one or more processorsdetermine that the left nasal cavity is not completely unblocked, thenthe one or more processors may indicate in the alert that the left nasalcavity is not completely unblocked. Similarly, if the one or moreprocessors determine that the right nasal cavity not completelyunblocked, then the one or more processors may indicate in the alertthat the right nasal cavity is not completely unblocked. The one or moreprocessors may cause the generated alert to be displayed on a displaydevice associated with monitoring device. The one or processors maygenerate an alert indicating one or more nasal cavities are notunhealthy

Turning now to FIG. 62, there is shown a process to adjust or modify auser interface based on location of the monitoring device. For thepurpose of illustrating a clear example, components of the monitoringsystem 1, and components of the respiration sensors 100 a, 100 b,previously described herein, may be used to describe the process ofadjusting or modifying a user interface based on a location of themonitoring device.

The method 6200 includes determining, by one or more processors of amonitoring device, a location of the monitoring device (block 6201). Insome implementations, the monitoring device may be configured with ageographical positioning system, and the one or more processors may beconfigured to determine a location of the monitoring device based ondata from the geographical position system related to locationinformation of the monitoring device. In some implementations, themonitoring device may be configured to receive location information fromone or more beacon devices, and the one or more processors may beconfigured to determine location of the monitoring device based on thelocation information received from one or more beacon devices. The oneor more processors may be configured to associate certain area or unitswithin a medical facility with certain location information. The one ormore processors may determine an area or unit with a medical facilitybased on the location information and the stored associations. Forexample, if a certain location information is associated with a generalward and certain other location information is associated with intensivecare unit, and if the received location information matches the locationinformation associated with the general ward, then the one or moreprocessors may determine that the current monitoring device is in thegeneral ward.

The one or more processors determine a user of the monitoring device(block 6202). The one or more processors may be configured to determinewhether any user is currently logged into the monitoring device. Forexample, based on a stored login data, the one or more processorsdetermine an identifier of a user that is currently logged in, and thebased on the identifier, the one or more processors may determine acurrent user of the monitoring device. The one or more processorsdetermine adjustments to the user interface based on the user and thelocation of the monitoring device (block 6203). The one or moreprocessors may be configured to track and store information related tovarious user interface adjustments made by a user over certain period oftime and associate such adjustments with the user and the location ofthe monitoring device. For example, a user, such as a nurse, may adjusta default user interface by adding certain graphical components and/orremoving certain graphical components, and the user may make theseadjustments over period of 15 days every time the user interacts with amonitoring device in a general ward area, then the one processors maytrack the addition and deletion of the graphical items and associatethese additions and deletions with the nurse and the general ward.

Based on the determined user of the monitoring device and the locationof the monitoring device, the one or more processors may determine theadjustments that may be made to the user interface. The one or moreprocessors modify the user interface based on the determined adjustments(block 6204). The one or more processors may modify the user interfaceby adding and/or deleting graphical components. Similarly, the one ormore processors may modify the user interface by adjusting size of thegraphical components, text displayed in the user interface, the mannerin which data is displayed to a user and the like. Thus, once the useris ready to interact with the monitoring device at a particular location(e.g., an intensive care unit), then the monitoring device automaticallymodifies the user interface in order to display a user interface thatthe user desires.

XII. Chronic Obstructive Pulmonary Disease (COPD) Monitoring

Turning now to FIG. 63, there is shown a process to predict a likelihoodof a patient experiencing a chronic obstructive pulmonary disease (COPD)exacerbation. In some implementations, an exacerbation of COPD may referto worsening of COPD symptoms. For the purpose of illustrating anexample, components of the monitoring system 1, and components of thesensor device 2 (including e.g., respiration sensors 100 a, 100 b),previously described herein, may be used to describe the process ofpredicting a likelihood of a patient experiencing a COPD exacerbation.As described above, in some implementations, a monitoring device 4 mayinclude a memory storage unit and/or may be communicatively coupled witha remotely located storage unit (e.g., a cloud-based storage unit). Oneor more processors of the monitoring device may be configured to storedata in any storage unit associated with the monitoring device.

The method 6300 includes receiving, by a monitoring device 4, motiondata (e.g., movement data) from a sensor device associated with apatient (block 6301). As described above, motion data may include datafrom an accelerometer (and/or gyroscope) of a sensor device, such as thesensor device 2. The motion data may indicate a movement of the patient.For example, the motion data may indicate whether a patient is moving orwhether a patient is at rest. In some implementations, the monitoringdevice 4 may determine a heart rate of a patient based on the motiondata.

The monitoring device 4 may determine a heart rate of the patient basedon the detected movements of the body of the patient. As describedabove, an accelerometer, such as the accelerometer 1150 (shown in FIG.41), of the sensor device, such as the sensor device 2, may beconfigured to detect back and forth cyclical movement of the body of apatient at the phase of a heartbeat of the patient. In someimplementations, the accelerometer 1150 of the sensor device 2 may beconfigured to detect the heart's rotation along its long-axis, whichalso generates rotational force around longitudinal axis of thepatient's body at a phase of the heartbeat. The monitoring device 4 maydetect the longitudinal movement or rotational movement around thepatient's body's longitudinal axis and determine a heartbeat orheartbeats per minute value from the data of the accelerometer. In someimplementations, the accelerometer 1150 can also detect rise and fall ofa patient's chest or other thoracic movement and determine a heart ratebased on the detected rise and fall of the patient's chest.

The monitoring device 4 receives physiological data of the patient fromthe sensor device (block 6302). The physiological data of the patientmay include data indicating breathing patterns from breathing sensors ofthe sensor device 2. In some implementations, the monitoring device 4may be coupled to one or more external medical devices, such as a pulseoximeter. The monitoring device 4 may receive physiological data thatincludes amount of oxygen in patient's blood from the one or moreexternal medical devices, such as the pulse oximeter. The monitoringdevice 4 may determine a level of activity of the patient based on thephysiological data. For example, the monitoring device 4 may determine alevel of activity of the patient based on the heart rate and/orperipheral capillary oxygen saturation (SpO₂) data of the patient. Alevel of activity may indicate a certain activity (e.g., walking,exercising, running, and the like) and may be associated with apredetermined activity category. Additional details of determining alevel of activity are described herein with reference to FIG. 64.

As described above, predetermined activity category may be associatedwith a level of activity. The monitoring device 4 may be configured todetermine a predetermined activity category based on a determined levelof activity. As shown in FIG. 63, the monitoring device 4 selects thepredetermined activity category from a plurality of predeterminedactivity categories (block 6303). The monitoring device 4 may beconfigured to receive location data related to the patient from sensordevice 2. The monitoring device 4 may determine a path travelled by thepatient based on the location data and the motion data of the patient.

In some implementations, the monitoring device 4 may be configured todetermine a number of times a patient travelled a path, and the one ormore processors of the monitoring device 4 may be configured to displaythe number of times the patient travelled a path in a GUI on a displaydevice associated with the monitoring device 4. In some implementations,the monitoring device 4 may be configured to generate a graphical pathline for each path travelled by the patient, and displays the generatedgraphical path lines on a GUI displayed on a display device associatedwith the monitoring device 4. The monitoring device 4 may be configuredto indicate a number of times the path travelled by the patient by asize of a graphical path generated. For example, for each time thepatient travelled a path, the monitoring device 4 may increase the sizeof the graphical path. Similarly, in some implementations, themonitoring device 4 may decrease size of the graphical path if a patientdoes not travel on a path for a threshold period of time. In someimplementations, the monitoring device 4 may be configured to determinewhether a patient travelled vertically based on the motion data. Asdescribed above, the motion data may include accelerometer data,positional data, and/or orientation data, and the monitoring device 4may determine whether a patient travelled vertically (e.g., going upstairs, going down stairs, and the like). The monitoring device 4 may beconfigured to display a vertical position of the patient in a GUI on adisplay device associated with the monitoring device 4.

In some implementations, the monitoring device 4 may be configured toassociate one or more baseline physiological values with a path. In someimplementations, the monitoring device 4 may associate a baselinephysiological value with a determined activity category of the patient.The monitoring device 4 may generate the baseline physiological valuebased on physiological data measured during a period of time the patienttraveled the associated path and/or during which the motion data of thepatient is collected and/or measured.

The monitoring device 4 identifies a baseline physiological value from aplurality of baseline physiological values (block 6304). The monitoringdevice 4 may be configured to identify the baseline physiological valuebased on the determined activity category and/or path travelled by thepatient. The monitoring device determines a difference between a valuein the physiological data and the identified baseline physiologicalvalue (block 6305). For example, the monitoring device 4 may calculate adifference between the baseline respiration rate and the respirationrate indicated by the received breathing pattern data. Similarly, themonitoring device 4 may calculate a difference between the baseline flowrate and the flow rate indicated by the received breathing pattern data.The monitoring device 4 predicts a likelihood of the patientexperiencing a COPD exacerbation (block 6306). The monitoring device 4may predict the likelihood based on the calculated difference betweenthe baseline flow rate and respiration rate and the flow rate andrespiration rate received from the data indicated by breathing patterndata.

While the above describes one or more processors of the monitoringdevice performing the process to predict a likelihood of a patientexperiencing a COPD exacerbation, one skilled in the art shouldrecognize that one or more processors of the sensor device may beconfigured to perform the process to predict a likelihood of a patientexperiencing a COPD exacerbation in accordance with the processdescribed in FIG. 63.

Turning now to FIG. 64, there is shown a process to determine anactivity level of a patient and associate the activity level with one ormore baseline physiological values. For the purpose of illustrating anexample, components of the monitoring system 1, and components of therespiration sensors 100 a, 100 b, previously described herein, may beused to describe the process of determining an activity level of apatient and associating the activity level with one or more baselinephysiological values.

The method of 6400 includes receiving, by one or more processors of amonitoring device 4, data indicating breathing patterns from breathingsensors of a sensor device of the patient (block 6401). As describedabove, the breathing pattern data may indicate breathing patterns frombreathing sensors associated with left nostril, right nostril, and/ormouth of the patient. In some implementations, the one or moreprocessors of the monitoring device 4 may determine a respiration rateand/or flow rate of the patient based on the received breathing patterndata. In some implementations, the received breathing pattern data mayinclude a respiration rate and/or flow rate of the patient. The one ormore processors of the monitoring device 4 receive motion data from asensor device associated with the patient (block 6402). The motion datamay include data from an accelerometer, such as the accelerometer 1170,of the sensor device. The received motion data may indicate howfrequently a patient is moving. The received motion data may be capturedand/or measured while the received breathing pattern data is collectedand/or measured. The one or more processors of the monitoring device 4may associate the received breathing pattern data with the receivedmotion data, and may store the received breathing pattern data inassociation with the received motion data in a storage unit associatedwith the monitoring device 4.

The one or more processors of the monitoring device 4 determines a heartrate of the patient (block 6403). The received motion data may includedata from an accelerometer, such as the accelerometer 1170, of thesensor device, such as the sensor device 2. As described above, the oneor more processors of the monitoring device 4 may determine a heart ratebased on the data from the accelerometer of the sensor device. The oneor more processors of the monitoring device 4 determines a level ofactivity of the patient (block 6404). The one or more processors of themonitoring device 4 may determine a level of activity of the patientbased on a heart rate of the patient. The monitoring device 4 may beconfigured with a set of rules that specify different levels of activityfor different ranges of heart rates.

For example, the set of rules may specify that a patient is moving if aheart rate of the patient is between a first range of heart rates, suchas a heart rate between 80 and 100, is resting or idle if the heart rateof the patient is between a second range of heart rates, such as a heartrate between 70 and 75, is sleeping if the heart rate is between a thirdrange of heart rates, such as a heart rate between 55 and 60, and isengaged in a high effort activity if the heart rate is between a fourthrange of heart rates, such as a heart rate between 110 and 175. Examplesof a high effort activity may include, but are not limited to, exercise,running, walking up and/or down a set of stairs, and the like. The oneor more processors of the monitoring device 4 may be configured todetermine a level of activity based on the set of rules and the heartrate of the patient.

In some implementations, for each level of activity, the set of rulesmay specify a threshold amount of time during which a heart rate ofpatient should satisfy the corresponding range of heart rates. Forexample, the set of rules may specify that a heart rate of a patientshould be between 80 and 100 for at least 5 seconds to determine thatthe patient is walking. In some implementations, the set of rules mayspecify different threshold amounts of time for different levels ofactivity. Continuing with the previous example, the set of rules mayspecify that a heart rate of a patient should be between 110 and 175 forat least 15 seconds to determine that the patient is engaged in a higheffort activity. The one or more processors of the monitoring device 4may be configured to determine a level of activity of the patient basedon whether a heart rate of a patient is within a range of heart ratesfor a threshold amount of time.

As described above, the sensor device, such as the sensor device 2, maybe configured to transmit data continuously in real-time or nearreal-time, and the one or more processors may be configured to store thedetermined heart rates of the patient in association with the time atwhich the heart rate is determined and/or the time at whichcorresponding accelerometer data is received and/or captured. The one ormore processors of the monitoring device 4 may be configured todetermine a level of activity of the patient by determining whether theheart rate of the patient is within a specified range of heart rates forthe level of activity for a corresponding threshold duration of timebased on the stored heart rates and their associated times. For example,the one or more processors of the monitoring device 4 may determinewhether the patient is engaged in a high effort activity by determiningwhether the heart rate of a patient is between 80 and 100 for at least 5seconds based on the stored heart rates for the past 5 seconds.

The one or more processors of the monitoring device 4 may be configuredto store the received breathing pattern data in association with thedetermined level of activity in a storage unit associate with themonitoring device. The one or more processors of the monitoring device 4generates a baseline physiological value (block 6405). The one or moreprocessors of the monitoring device may be configured to determine abaseline physiological value based on corresponding physiological valuesover a threshold period of time. As described above, examples ofphysiological values may include, but are not limited to, respirationrate of a patient, a flow rate of the patient, and the like.

As described above, in some implementations, the received breathingpattern data may include respiration rate of the patient and/or flowrate of the patient, and the one or more processors of the monitoringdevice 4 may be configured to store the respiration rate and/or flowrate in association with information related to a time at which therespiration rate and/or flow rate is captured and/or measured. Forexample, if the threshold period of time is 30 days, then the one ormore processors of the monitoring device 4 may determine a baselinerespiration rate based on respiration rates of the patient over the last30 days. Similarly, if the threshold period of time is 30 days, then theone or more processors of the monitoring device may determine a baselineflow rate based on the flow rates of the patient over the last 30 days.

In some implementations, the one or more processors of the monitoringdevice 4 may determine whether the determined level of activity isassociated with a baseline physiological value. If the determined levelof activity is associated with a baseline physiological value, then theone or more processors of the monitoring device may be configured togenerate a new baseline physiological value by updating the associatedbaseline physiological value based on the received breathing patterndata. For example, if the determined level of activity of the patient isassociated with a baseline respiration rate and a baseline flow rate,then the one or more processors of the monitoring device 4 may generatea new baseline respiration rate and a new baseline flow rate based onthe received respiration rate and received flow rate, respectively.

The one or more processors of the monitoring device 4 may associate thegenerated baseline physiological value with the determined level ofactivity (block 6406). For example, if the determined level of activityof the patient is moving, then the one or more processors may store thegenerated baseline respiration rate in association with the determinedlevel of activity. Similarly, the one or more processors may store thegenerated baseline flow rate in association with the determined level ofactivity.

While the above describes one or more processors of the monitoringdevice performing the process to determine an activity level of apatient and associate the activity level with one or more baselinephysiological values, one skilled in the art should recognize that oneor more processors of the sensor device may be configured to determinean activity level of a patient and associate the activity level with oneor more baseline physiological values in accordance with the processdescribed in FIG. 64.

Turning now to FIG. 65, there is shown a process to determine a pathtraveled by the patient and associate the path with one or more baselinephysiological values. For the purpose of illustrating an example,components of the monitoring system 1, and components of the respirationsensors 100 a, 100 b, previously described herein, may be used todescribe the process of determining a path traveled by the patient andassociate the path with one or more baseline physiological values.

The method 6500 includes determining, by one or more processors of amonitoring device 4, location of a patient (block 6501). As describedabove, in some implementations, the monitoring device may be configuredwith a geographical positioning system, and the one or more processorsmay be configured to determine a location of the monitoring device basedon data from the geographical position system related to locationinformation of the monitoring device. In some implementations, themonitoring device may be configured to receive location information fromone or more beacon devices, and the one or more processors may beconfigured to determine location of the monitoring device based on thelocation information received from one or more beacon devices.

The one or more processors may be configured to associate an area (e.g.,kitchen, living room, bedroom, and the like) of a patient's home withlocation information. The one or more processors may determine an areaof a patient's home based on the location information and the storedassociations. For example, if location information is associated withthe kitchen and other location information is associated with livingroom, and if the received location information matches the locationinformation associated with the kitchen, then the one or more processorsmay determine that the current monitoring device is in the kitchen.

The one or more processors of the monitoring device 4 receive motiondata from a sensor device associated with a patient (block 6502). Asdescribed above, the one or more processors of the monitoring device 4,determine a level of activity of the patient based on the motion data.The one or processors of the monitoring device 4 determine a pathtraveled by the patient (block 6503). The one or more processors of themonitoring device 4 determine the path based on the determined locationof the patient and the received motion data. For example, the one ormore processors may determine whether the patient is moving anddetermine a second location of the patient based on the movement of thepatient. In some implementations, the motion data from the sensor devicemay include acceleration, position, angular rotation, and/or orientationdata related to the patient, and the one or more processors of themonitoring device may determine whether the patient is travelling in avertical direction based on the acceleration, position, angularrotation, and/or orientation data related to the patient.

In some implementations, the monitoring device 4 may be configured withone or more machine learned models that are trained to detect pathstravelled by a patient. The one or more machine learned models may betrained with inputs from a sensor device, such as motion data, breathingpatterns of a person associated with the sensor device, and the like. Insome implementations, the one or more machine learned models may betrained to detect stairs or other structures based on the movement dataof the patient. For example, the one or more machine learned models maybe trained to detect stairs based on orientation data received from thesensor device, and the patient moving vertically. In someimplementations, the one or more machine learned models may be trainedto detect obstacles (e.g., couch, table, and the like) in a pathtravelled by the patient.

The one or more processors may be configured to generate a graphicalrepresentation of a bounded area, such as a virtual map or a virtualfloor plan of a structure where the patient resides. As described above,the one or more processors may be configured to generate graphical linesthat indicate the paths travelled by the patient. The one or moreprocessors may include the generated graphical lines in the generatedgraphical representation of the bounded area. An example of a generatedgraphical representation of a bounded area including the graphicalrepresentation of paths travelled by a patient is shown in FIG. 66A. Asshown in FIG. 66A, graphical representation of bounded area 6600includes graphical generated paths 6605, 6606. In some implementations,a user and/or a patient may provide inputs to a monitoring device thatindicate location information, such as kitchen 6601, living room 6602,bedroom 6604, and the like, for certain portions of the graphicalrepresentation of the bounded area, and the one or more processors ofthe monitoring device may display the location information in thegenerated graphical representation of a bounded area, as shown in FIG.66A.

The one or more processors of the monitoring device generate a baselinephysiological value (block 6504). As described above, the one or moreprocessors of the monitoring device may determine a baselinephysiological value, such as a baseline respiration rate value and/orbaseline flow rate value, based on the respiration rate data, and flowrate data, respectively. The one or more processors of the monitoringdevice associate the generated baseline physiological value with thedetermined path (block 6505). The one or more processors of themonitoring device may store the generated physiological value inassociation with the determined path in a storage device associated withthe monitoring device.

In some implementations, an existing baseline physiological value may beassociated with the determined path, and an indicator may be stored in amemory of the monitoring device indicating that the determined path isassociated with a baseline physiological value. The one or moreprocessors of the monitoring device may identify existing baselinephysiological value based on the determined path, and generate a newbaseline physiological value by updating the existing baselinephysiological value associated with the determined path based onreceived physiological data. For example, as described above, the one ormore processors of the monitoring device may generate a new baselinerespiration rate by updating an existing baseline respiration rate basedon the respiration rate data. Similarly, the one or more processors maygenerate a new baseline flow rate by updating an existing baseline flowrate based on the flow rate data. The one or more processors of themonitoring device may associate the generated new baseline physiologicalvalue with the determined path.

While the above describes one or more processors of the monitoringdevice performing the process to determine a path traveled by thepatient and associate the path with one or more baseline physiologicalvalues, one skilled in the art should recognize that one or moreprocessors of the sensor device may be configured to determine a pathtraveled by the patient and associate the path with one or more baselinephysiological values in accordance with the process described in FIG.65.

FIG. 66B illustrates a first graphical display of real time measurementsfor indicating whether a patient is likely to experience a health event,according to various aspects of the subject technology. The patient'sphysiological parameters measured with the sensor device 2. For example,respiration flow (Flow), respiration rate (RR), the sensor location onface, as well as position/movement (e.g., head posture/movement,walking, falling down), and hear rate (HR) may be determined aspreviously described above. The patient's location may also be detectedand tracked based on various technologies (e.g., within the device or incommunication with various aspects of the system). For example, locationmay be detected using SiLabs BTLE tracking device, Wifi tracking, GPS,and the like. In this regard, monitoring device 4 may determine thepatient's real time location, movement, path, and time used for themovement.

The device and system of the subject technology enable the patient'slocation and movement in a house can be detected with less than 25 cmaccuracy (e.g., using BTLE tracking, which may include three dimensionalvector with direction (α, β) and length L=>location/speed). Thislocation information can then be mapped with the layout of patient'shouse, as described above. Changes in patient's efforts can beapproximated by combining patient's location/movement & time with theparameter data from the sensors. Oxygenation can also be detected, whichmay affect to efforts of working approximations. Approximations may thenbe made and graphically displayed as in FIGS. 66A and 66B.

In the depicted example, the patient may be resting for a period of time(“Resting”). A rest state measurement may include, for example, nomovement by the patient over a period of time (α, β, L constant). Forexample, the patient may be watching television (e.g., on a couch) inthe living room. The monitoring device 4 may identify the location as acouch and/or living room based on previously inputted data for thepatient and location data received from sensor device 2. In the depictedexample, location and sensor information are recorded for example for 10minutes to get rest state trend in the living room. Data received fromthe sensor device 2 shows that patient is in the upright position(sitting), but no movement. RR and flow are constant, as well as HR. Themonitoring device 4 determines, based on a combination of these factors,that the patient is resting, and the designation is visually indicatedon the graphical display of FIG. 66B.

The graphical display depicts an amount of flow or respiration over aperiod of time. IN the depicted example, the period of time is one hour.In some sub-periods of time during the example hour, no sensor activitymay be detected. For example, the patient may go in to the kitchen toeat. In this regard, the patient location detection shows movement fromthe couch in the living room to the kitchen chair (α, L) and no movementafter that (α, β, L constant). The sensor first shows upright positionand walking (steps). Then the sensor device 2 detects that the patientis in the upright position and location on the chair. From this data themonitoring device 4 may indicate that the patient is sitting on thechair by the kitchen table.

During another period, the sensor location shows that sensor is not onthe face (RR, Flow and HR=0) and measurement is stopped. From this data,the monitoring device may indicate that the patient took the sensor awayfrom the face for the time of eating. The sensor location then showsthat sensor is on the face again (RR, Flow and HR≠0) and measurement isstarted again. The patient placed the sensor on the face again. All ofthese events may be presented as graphical indicators in the graphicaldisplay.

In one period the patient is shown to be striving (“Striving”). In thisregard, the measured data indicates that the patient climbs to upstairsinto the bedroom to sleep, and the graphical display indicatesmeasurements during high effort. In association with this period, thelocation data indicates that the patient is moving through the livingroom towards the stairs (α, L). The data further indicates that patientis in the upright position and walking (steps). RR, flow and HR ismarkedly increased due to the effort by the patient. The monitoringdevice 4 determines, based on a combination of these factors, that thepatient is striving, and the designation is visually indicated on thegraphical display.

The monitoring device 4 detects, based on the location data, that thepatient is close to the first step of the (pre-programmed) stairs.Location and sensor information recording may be ongoing, or started(e.g., at a higher rate) at this time. The monitoring device 4 detectsmovement through the stairs and climbing (α, β, L). RR, flow and HRincrease, and the sensor data shows the patient in an upright positionand walking (steps). The monitoring device 4 then detects and visuallyindicates that the that patient is close to the last step of the stairs.At this point, the location and sensor information recording may bereduced in frequency or paused/stopped.

In one period the patient is shown to be sleeping (“Sleeping”). In thisregard, the location data indicates that patient is moving towards theliving room upstairs (α, L) and finally reaches the bed. The sensorshows that patient is in the upright position and walking (steps) andfinally lays down. RR, flow and HR start to decrease. The monitoringdevice 4 determines, based on a combination of these factors, that thepatient is sleeping, and the designation is visually indicated on thegraphical display. According to the depicted example, location andsensor information recording may be started when when patient's positionstationary, laying down and breathing stable (for example RR and flowvariance <1 and HR variability <10).

FIG. 66C illustrates a second graphical display of real timemeasurements for indicating whether a patient is likely to experience ahealth event, according to various aspects of the subject technology.The depicted example, graphical display visually indicates the patientbaseline, and where a limit has been exceeded. Graphical display furtherdepicts when the deviation from the baseline is representative of apatient exacerbation or health event. On detecting the patientexacerbation or health event, monitoring device 4 may provide a visualindication or alert on graphical display (“Exacerbation”) that isdistinguishable from other indications on the display. In someimplementations, detection of the patient exacerbation or health eventmay further cause monitoring device 4 to provide a notification to aremote device, such as a mobile device of a caregiver associated withthe patient.

XIII. Sensor Rise Times

Turning now to FIG. 67, there is shown a detailed view of an electronicsassembly 6700 for a sensor device, such as sensor device 2. As describedabove, sensor device 2 may be any of a respiration sensor 100 a, 100 b,100 c. The electronics assembly 6700 may include support structures,such as support structure 6702. Examples of support structure 6702 mayinclude support structures 1230-1, 1230-2, 1230-3, as shown in FIG. 30.The support structure 6702 may be configured to support sensors, such assensor 6704. Examples of sensor 6704 may include, but are not limitedto, thermistors, such as thermistors 400-1, 400-2, 400-3, as shown inFIG. 30, thermocouples, and the like.

In some implementations, as described above, the support structure 6702may include electrically and/or thermally insulating material. In someimplementations, the support structure 6702 may include, but are notlimited to, fiberglass, epoxy resin, flame retardant material, and thelike, and/or any combination thereof. In some implementations, thermalconductivity of the materials of the support structure 6702 may be lessthan 0.29 watt/(meter*kelvin) (W/(m*K)). In some implementations, thethermal conductivity of the support structures may be between 0.29W/(m*K) and 0.343 W/(m*K).

As shown in FIG. 67, size of the support structure 6702 may be of alength A′, a width B′, and of a thickness or a height C′. In someimplementations, a length A′ of the support structure 6702 may bebetween 10 millimeters (mm) and 50 mm. For example, the length A′ of thesupport structure 6702 may be 20 mm. In some implementations, a width B′of the support structure 6702 may be between 0.1 mm and 5 mm. Forexample, the width B′ of the support structure 6702 may be 1 mm. Athickness or height C′ of the support structure 6702 may be between 0.01mm and 0.5 mm. For example, the thickness or height C′ of the supportstructure 6702 may be 0.1 mm.

The support structure 6702 may be electrically connected to theelectronics board 6701. For example, the support structure 6702 may besoldered to the electronics board 6701, such as at position 6705, toform electrical connections between the electrical connection ofelectronics board 6701, such as electrical connections 6706, and theelectrical connections of the support structure, such as electricalconnections 6703. In some implementations, width of the electricalconnection 6703 may be between 25 μm and 200 μm. For example, the widthof the electrical connection 6703 may be 150 μm. In someimplementations, thickness of the electrical connection 6703 may bebetween 5 μm and 50 μm. For example, the thickness of the electricalconnection 6703 may be 30 μm. In some implementations, electricalconnections 6703 and 6704 may comprise electrical wires. The material ofelectrical wires of the electrical connections 6703 and 6704 may becopper.

The sensor 6704 may be electrically connected to the support structure6702. For example, the sensor 6704 may be soldered to the electricalconnections 6703 of the support structure 6702. In some implementations,a length of the sensor 6704 may be between 0.1 mm and 2 mm. For example,the length of the sensor 6704 may be 1 mm. In some implementations, awidth of the sensor 6704 may be between 0.1 mm and 1 mm. For example,the width of the sensor 6704 may be 0.5 mm. In some implementations, athickness or height of the sensor 6704 may be between 0.1 mm and 1 mm.For example, the thickness or height of the sensor 6704 may be 0.5 mm.

Materials included in the components surrounding the sensor 6704, and/orsize of the components surrounding the sensor 6704 may affect thethermal mass surrounding the sensor 6704. Thermal mass surrounding thesensor 6704 may affect a rise time of the sensor 6704, and/or a responsetime of the sensor 6704. For example, an increase in thermal mass mayresult in an increased rise time and/or a slower response time of thesensor 6704. Similarly, a decrease in thermal mass may result in adecreased rise time and/or faster response time of the sensor 6704. Insome implementations, as referred to herein a rise time of a sensor maybe the time taken to change from a first value to a second value. Insome implementations, the first value may be a first percentage of afinal output value of the sensor, and the second value may be a secondpercentage of the final output value. For example, the first value maybe 10% of the final output value of the sensor 6704, and the secondvalue may be 90% of the final output value.

In some implementations, thermal mass surrounding the sensor 6704 may bereduced by using materials with very low thermal conductivity and/orvery high thermal insulating properties in the components surroundingthe sensor. For example, thermal mass of support structure 6702 may bereduced by using materials with a thermal conductivity of less than 0.29W/(m*K). In some implementations, the thermal mass surrounding a sensormay be reduced by reducing the size and/or dimensions of the componentsaround the sensor 6704. For example, as shown in FIG. 68, the size ofthe support structure 6702 may be reduced by reducing the width B′ andthickness C′ of the support structure 6702. As an example, the width B′of the support structure 6702 may be reduced to 0.7 mm and the thicknessC′ of the support structure may be reduced to 0.08 mm.

In some implementations, the thermal mass surrounding the sensor 6704may be reduced by reducing size of the electrical connections 6703. Forexample, a width of an electric connection may be reduced to 50 μm and athickness of the electric connection may be reduced to 14 μm. In someimplementations, the thermal mass surrounding the sensor 6704 may bereduced by reducing size of the sensor 6704. For example, the size ofthe sensor 6704 may be reduced to have a length of 0.5 mm, a width of0.25 mm, and a thickness of 0.25 mm. In some implementations, thethermal mass surrounding the sensor 6704 may be reduced based on apattern of the electrical connection 6703. For example, the electricalconnection 6703 may be implemented on the support structure 6702 in anundulated pattern, as shown in FIG. 68.

Reducing the thermal mass surrounding the sensor 6704 may optimize thesensitivity of the sensor 6704 to thermal changes. In someimplementations, the improvement to sensitivity of the sensor 6704 mayconfigure the sensor 6704 to detect thermal changes across a range ofbreath frequencies and/or respiration rates of the patient. For example,if the sensor 6704 is a thermistor, such as the thermistor 401-1 (shownin FIG. 30), then the sensor 6704 may detect thermal changes atrespiration rates of 120 breaths per minute (bpm) or greater. Similarly,the sensor 6704 may detect thermal changes at respiration rates of 10bpm or less. In some implementations, the sensor 6704 may also detectthermal changes between respiration rates of 10 bpm and 120 bpm.

In some implementations, a rise time of the sensor 6704 may be between0.3 degrees Celsius per second (° C./s) and 2.6° C./s. For example, therise time of the sensor 6704 may be 0.32° C./s. In some implementations,a rise time of the sensor 6704 may be between 0.7° C./s and 1.6° C./s.In some implementations, it may be preferred to have a high responsetime to detect changes in temperatures more rapidly and the rise time ofthe sensor 6704 may be preferred to be between 0.7° C./s and 1.6° C./s.For example, the rise time of the sensor 6704 may be 0.77° C./s. In someimplementations, it may be preferred to capture more detailed changes intemperatures at very high respiration rates (e.g., 120 breaths perminute) and the rise time of the sensor 6704 may be preferred to begreater than 1.29° C./s, such as between 1.3° C./s and 1.6° C./s.

In some implementations, a sensor device 2, (including e.g., respirationsensors 100 a, 110 b) may be configured with a sensor to measure SpO2and/or oxygen saturation of a patient. An example of the sensor device 2configure with a sensor to measure SpO2 and oxygen saturation of apatient is shown FIG. 69. In FIG. 69, sensor 6902 may be coupled to aframe sensor device, such as frame 320, as described above withreference to FIG. 28. The sensor 6902 may be placed against a lip 6910of a patient when the patient wears the sensor device.

The sensor 6902 may be configured with at least one light emitting diodeconfigured with emitting a red light 6904-1 and at least one lightemitting diode emitting an infrared light 6904-2. The sensor 6902 may beconfigured to transmit the red light 6904-1 and the infrared light6904-2. When transmitted from the sensor 6902, the red light 6904-1 andthe infrared light 6904-2 transmit through the lip 6910 of the patientand reflect off a bone behind the lip 6910 of the patient, such as bone6912 of the patient.

The sensor 6902 may be configured with a red light detector 6908-1 andan infrared light detector 6908-2, and the reflected red light 6906-1may be detected and/or measured by the red light detector 6908-1 and thereflected infrared light 6906-2 may be detected and/or measured by theinfrared light detector 6908-2. The sensor 6902 may be configured tocalculate the levels of the measured red light and infrared light. Thesensor 6902 may be configured to calculate oxygen saturation based onthe calculated levels of the red light and the infrared light.

Illustration of Subject Technology as Clauses

Various examples of aspects of the disclosure are described as numberedclauses (1, 2, 3, etc.) for convenience. These are provided as examples,and do not limit the subject technology. Identifications of the figuresand reference numbers are provided below merely as examples and forillustrative purposes, and the clauses are not limited by thoseidentifications.

Clause 1. A respiration sensor comprising: a housing having a firstnasal flow passage and a second nasal flow passage that extendtherethrough, wherein the first and second nasal flow passages aredisposed in parallel to one another with respect to a nasal respiratoryflow direction; and an electronics board comprising a first nasalthermistor and a second nasal thermistor, the electronics board coupledto the housing such that the first and second nasal thermistors arepositioned into each of the first and second nasal flow passages,respectively.

Clause 2. The respiration sensor of Clause 1, wherein the electronicsboard comprises a support structure, the support structure having aproximal portion coupled to the electronics board and a distal portiontransverse to a plane defined by a top of the electronics board,wherein, when the electronics board is positioned within the housing,the distal portion of the support structure extends into at least one ofthe first and second nasal flow passages.

Clause 3. The respiration sensor of Clause 2, wherein any of the firstor second nasal thermistors are coupled to the distal portion of thesupport structure.

Clause 4. The respiration sensor of any of Clauses 1 and 2, furthercomprising an oral flow passage and an oral thermistor, the oral flowpassage disposed transverse to the first and second nasal flow passages,along an oral respiratory flow direction.

Clause 5. The respiration sensor of Clause 4, wherein the electronicsboard comprises a support structure having a proximal portion coupled tothe electronics board and a distal portion extending along a planedefined by a top of the electronics board wherein, when the electronicsboard is positioned within the housing, the distal portion of thesupport structure extends into at least one of the first and secondnasal flow passages.

Clause 6. The respiration sensor of Clause 5, wherein the oralthermistor is coupled to the distal portion of the support structure.

Clause 7. The respiration sensor of any of Clauses 4 to 6, furthercomprising at least one oral flow guide disposed in the oral flowpassage.

Clause 8. The respiration sensor of Clause 7, wherein a first oral flowguide of the at least one oral flow guide is disposed proximate an oralinlet of the oral flow passage and a second oral flow guide of the atleast one oral flow guide is disposed proximate an oral outlet of theoral flow passage.

Clause 9. The respiration sensor of Clause 8, wherein any of the oralinlet and the oral outlet is elliptical.

Clause 10. The respiration sensor of any of Clauses 8 and 9, wherein theoral flow passage tapers from the oral inlet toward the oral outlet.

Clause 11. The respiration sensor of any of Clause 1 to 10, furthercomprising a third thermistor and a fourth thermistor, wherein the thirdthermistor is an ambient thermistor and the fourth thermistor is a skinthermistor configured to determine whether the respiration sensor isproperly positioned against a patient's physiognomy.

Clause 12. The respiration sensor of Clause 11, wherein the electronicsboard further comprises a filter configured to subtract a firstelectrical signal detected by the skin thermistor from a secondelectrical signal detected by the ambient thermistor.

Clause 13. The respiration sensor of any of Clauses 11 and 12, whereinthe electronics board further comprises a filter configured to subtracta first electrical signal detected by the skin thermistor and a secondelectrical signal detected by any of the first and second nasalthermistors and an oral thermistor from a third electrical signaldetected by the ambient thermistor.

Clause 14. The respiration sensor of any of Clauses 1 to 13, furthercomprising a shroud configured to protect the electronics board and toform at a least a portion of the first and second nasal flow passages.

Clause 15. The respiration sensor of any of Clauses 1 to 14, wherein theelectronics board further comprises an accelerometer configured todetect movement of the respiration sensor.

Clause 16. The respiration sensor of Clause 15, wherein theaccelerometer is configured to determine whether the respiration sensorhas fallen from a face of a patient or the patient has fallen.

Clause 17. The respiration sensor of any of Clauses 1 to 16, wherein theelectronics board further comprises a radio transceiver configured tocommunicate with an external device that is coupled with a network.

Clause 18. The respiration sensor of any of Clauses 2 to 17, wherein theelectronics board comprises a capacitive sensor configured to detect acontact between the housing and a patient's face, when the respirationsensor is in condition for use.

Clause 19. The respiration sensor of any of Clauses 1 to 18, furthercomprising at least one nasal flow guide disposed in each of the firstand second nasal flow passages.

Clause 20. The respiration sensor of Clause 19, wherein a first nasalflow guide of the at least one nasal flow guide is disposed proximate anasal inlet of one of the first and second nasal flow passages, and asecond nasal flow guide of the at least one nasal flow guide is disposedproximate a nasal outlet of the one of the first and second nasal flowpassages.

Clause 21. The respiration sensor of any of Clauses 1 to 20, furthercomprising a battery.

Clause 22. A respiration sensor comprising: one or more thermistorsconfigured to detect at least one of an inspiratory temperature, anexpiratory temperature, an ambient temperature adjacent the respiratorysensor, or a temperature of a patient's skin engaged against therespiration sensor; an accelerometer configured to detect at least oneof a movement of the patient, a position of the patient, a heart rate,or a respiration rate; and an electronics board coupled to the one ormore thermistors and the one or more thermistors.

Clause 23. The respiration sensor of Clause 22, comprising a thermistorconfigured to detect a temperature of a patient's skin engaged againstthe respiration sensor.

Clause 24. The respiration sensor of Clause 22, comprising a EtCO2sensitive surface configured to detect the presence of CO2.

Clause 25. A system, comprising: a server having a memory storingcommands, and a processor configured to execute the commands to:receive, from a hub, a data indicative of a respiratory condition of apatient; transfer the data into a memory in a remote server; provide thedata to a mobile computer device, upon request; and instruct the mobilecomputer device to graphically display the data, wherein the datacomprises a temperature value from at least one of two nasal flowpassages, a temperature value from an oral flow passage, a temperaturevalue of a patient's skin surface, and a temperature value of apatient's environment.

Clause 26. The system of Clause 25, wherein the processor is configuredto determine a respiration rate from the data indicative of therespiratory condition of a patient.

Clause 27. The system of any of Clauses 25 to 26, wherein the processoris configured to determine a respiration magnitude from the dataindicative of the respiratory condition of a patient.

Clause 28. The system of any of Clauses 25 to 27, wherein the processoris configured to determine a probability of a patient having a stroke orthe patient being under an opioid based on a variance of the dataindicative of the respiratory condition of a patient.

Clause 29. A method, comprising: receiving, from a hub, a dataindicative of a respiratory condition of a patient; transferring thedata into a memory in a remote server; providing the data to a monitor,upon request; and instructing the monitor to graphically display thedata, wherein the data comprises a temperature value from at least oneof two nasal flow passages, a temperature value from an oral flowpassage, a temperature value of a patient's skin surface, and atemperature value of a patient's environment.

Clause 30. The method of Clause 29, further comprising determining arespiration rate from the data indicative of the respiratory conditionof a patient.

Clause 31. The method of any of Clauses 29 to 30, further comprisingdetermining a respiration magnitude from the data indicative of therespiratory condition of a patient.

Clause 32. The method of any of Clauses 29 to 31, further comprisingdetermining a probability of a patient having a stroke or the patientbeing under an opioid based on a variance of the data indicative of therespiratory condition of a patient.

Clause 33. The method of any of Clauses 29 to 32, further comprisingassociating, in the remote server, a patient record with the respiratorycondition of the patient.

Clause 34. The method of any of Clauses 29 to 33, wherein the patient isone of a hospital patient or a home-care patient, the method furthercomprising alerting an emergency care unit when the respiratorycondition of the patient indicates a catastrophic event.

Clause 35. A respiration sensor system comprising: a respiration sensorcomprising a housing having a nasal flow passage that extendstherethrough, wherein the nasal flow passage is aligned with a nasalrespiratory flow direction, and an electronics board comprising a nasalthermistor, the electronics board coupled to the housing such that thenasal thermistor is positioned into the nasal flow passage; and a hubconfigured to move data between the respiration sensor and a network.

Clause 36. The respiration sensor system of Clause 35, wherein the hubis a smartphone.

Clause 37. The respiration sensor system of Clause 35, furthercomprising a monitor configured to receive data from an of therespiration sensor and the hub.

Clause 38. A method, comprising: monitoring data using a respirationsensor; receiving, by a hub separate from the respiration sensor, datafrom a respiration sensor; transmitting, from the hub to a network, thedata from the respiration sensor; and transmitting, from the network toa monitor, the data from the respiration sensor.

Clause 39. The method of Clause 38, wherein the data monitored by therespiration sensor is monitored via at least one of a skin thermistor,an ambient thermistor, at least one nasal thermistor, an oralthermistor, an accelerometer, and a breath indicator.

Clause 40. The method of Clause 39, further comprising receiving, by thehub from the respiration sensor, a notification indicating acorrectly-placed-no-breath state, wherein receiving the notification isin response to the respiration sensor determining that the skinthermistor is detecting a skin temperature, the ambient thermistor isdetecting an ambient air temperature, one of the at least one nasalthermistor and the oral thermistor is detecting the ambient airtemperature, and the breath indicator is detecting breaths.

Clause 41. The method of any of Clauses 39 to 40, further comprisingreceiving, by the hub from the respiration sensor, a notificationindicating a loose state, wherein receiving the notification is inresponse to the respiration sensor determining that the skin thermistoris detecting an ambient air temperature, the ambient thermistor isdetecting the ambient air temperature, one of the at least one nasalthermistor and the oral thermistor is detecting a gas flow temperature,and the breath indicator is detecting breaths.

Clause 42. The method of any of Clauses 39 to 41, further comprisingreceiving, by the hub from the respiration sensor, a notificationindicating any of a detached or no breath state, wherein receiving thenotification is in response to the respiration sensor determining thatthe skin thermistor is detecting an ambient air temperature, the ambientthermistor is detecting the ambient air temperature, one of the at leastone nasal thermistor and the oral thermistor is detecting the ambientair temperature, and the breath indicator is detecting no breaths.

Clause 43. The method of any of Clauses 39 to 42, further comprisingreceiving, by the remote hub from the respiration sensor, a notificationindicating an operating temperature exceeded state, wherein receivingthe notification is in response to the respiration sensor determiningthat the skin thermistor is detecting a skin temperature and the ambientthermistor is detecting a temperature equal to or greater than the skintemperature.

Clause 44. A method, comprising: measuring, by a first sensor device, aphysiological parameter of a patient proximate to the first sensordevice; automatically broadcasting, by the first sensor device,responsive to measuring the physiological parameter, a wirelessadvertisement signal configured to facilitate a pairing process betweenthe first sensor device and a first monitoring device; receiving, by thefirst sensor device after broadcasting the wireless advertisementsignal, a wireless request to perform the pairing process between thefirst sensor device and the first monitoring device; and automaticallycompleting the pairing process responsive to receiving the wirelessrequest.

Clause 45. The method of Clause 44, further comprising: receiving,during the pairing process, a patient identifier of a patient, whereinthe patient identifier is collected prior to the pairing process beinginitiated; and completing the pairing process based on receiving thepatient identifier.

Clause 46. The method of Clause 45, further comprising: automaticallyassociating, by the first sensor device, responsive to receiving thepatient identifier, the patient identifier with an identifier associatedwith the first sensor device.

Clause 47. The method of any of Clauses 44 to 45, further comprising:prior to broadcasting the wireless advertisement signal, determiningwhether a value of the measured physiological parameter satisfies athreshold physiological parameter value; and automatically transmittingthe wireless advertisement signal when the value of the measuredphysiological parameter satisfies the threshold physiological parametervalue.

Clause 48. The method of Clause 47, wherein the value of the measuredphysiological parameter satisfying the threshold physiological parametervalue requires a predetermined number of measurements of thephysiological parameter being at or above a predetermined value.

Clause 49. The method of any of Clauses 44 to 48, further comprising:receiving, at the first sensor device, data related to a colorassociated with the first sensor device from the monitoring device, anddisplaying the color on an LED of the first sensor device.

Clause 50. The method of clause 49, further comprising: providing, bythe sensor device to the monitoring device, before receiving the datarelated to the color, an identifier associated with the first sensordevice, wherein the color is based on the identifier associated withfirst sensor device.

Clause 51. The method of clause 49, wherein the color is determinedbased on colors associated with other sensor devices within a thresholddistance of the first sensor device.

Clause 52. The method of any of Clauses 44 to 51, further comprising:detecting a loss of a wireless connection to the first monitoringdevice; receiving, responsive to broadcasting a second wirelessadvertisement signal, a second wireless request to perform a secondpairing process between the first sensor device and a second monitoringdevice; transmitting, immediately after completing the second pairingprocess, the patient identifier to the second monitoring device; andcausing association of the second monitoring device with the patient.

Clause 53. A method comprising: receiving, by a monitoring device,breathing data indicating a breathing pattern of a patient and motiondata indicating a movement of the patient while the breathing data iscollected; comparing, by the monitoring device, the motion data and oneor more predetermined motion patterns associated with a lip movement;determining, by the monitoring device, based on the comparison, that themotion data was collected when the patient is talking; and adjusting, bythe monitoring device, based on the determination, the breathing data.

Clause 54. The method clause 53, further comprising: determining, by themonitoring device, based on the received breathing data, a currentplacement location of the sensor device on a face of the patient; andinitiating the step of comparing the motion data and the one or morepredetermined motion patterns associated with the lip movement, inresponse to determining the placement location of the sensor device.

Clause 55. The method of clause 54, wherein the placement location is alocation within a predetermined distance of a lip of the patient.

Clause 56. The method of clause 53, further comprising: determining, bythe monitoring device, a similarity level between the motion data and atleast one of the one or more predetermined motion patterns; determiningthat the motion data was collected when the patient is talking based onthe similarity level satisfying a threshold similarity level; andadjusting, by the monitoring device, the breathing data based ondetermining that the motion data was collected when the patient istalking.

Clause 57. The method of clause 53, further comprising: receiving, bythe monitoring device, from the sensor device, audio data collected by amicrophone of the sensor device while the breathing data is collected;determining, by the monitoring device, based on the audio data and thecomparison, that the patient is talking; and; adjusting, by themonitoring device, the breathing data based on determining that themotion data was collected when the patient is talking.

Clause 58. The method of clause 57, further comprising: determining, bythe monitoring device, whether a decibel level of the audio datasatisfies a threshold decibel level; and initiating the step ofcomparing the motion data and the one or more predetermined motionpatterns in response to determining the decibel level satisfies thethreshold decibel level.

Clause 59. The method of clause 53, further comprising: determining, bythe monitoring device, a difference between the breathing data andbaseline breathing data indicating baseline breathing patterns of thepatient; determining, by the monitoring device, whether the differencesatisfies a threshold difference; and; adjusting, by the monitoringdevice, based on the determination that the difference satisfies thethreshold difference and the determination that the patient is talking,the breathing data.

Clause 60. The method of clause 59, wherein the breathing data isadjusted to reduce the difference and satisfy the threshold difference.

Clause 61. The method of clause 59, wherein the breathing data isreceived for a first period of time.

Clause 62. The method of clause 61, further comprising: determining, bythe monitoring device, the baseline breathing data based on breathingdata indicating breathing patterns of the patient for a second period oftime, wherein the second period of time occurs prior to the first periodof time.

Clause 63. A method comprising: receiving, by a monitoring device, froma sensor device, breathing data indicating a breathing pattern of apatient and motion data indicating a movement of the patient while thebreathing data is collected; determining, by the monitoring device,based on the received motion data and the received breathing data, aposition of the sensor device on a face of the patient in athree-dimensional space; and providing, by the monitoring device, fordisplay on a display device, a graphical representation of the position.

Clause 64. The method of clause 63, further comprising: comparing themotion data and the breathing data with one or more predetermined sleeppatterns, at least one of the one or more predetermined sleep patternsassociated with an indication of sleep apnea; generating an apnea score,by the monitoring device, based on the comparing, indicating alikelihood that the patient is experiencing sleep apnea; generating analert when the generated apnea score satisfies a threshold likelihoodlevel; and providing, by the monitoring device, for display on thedisplay device, an indication of the alert together with the graphicalrepresentation of the position.

Clause 65. The method of clause 63, further comprising: determining, bythe monitoring device, based on the breathing data, a first breathingpattern indicating a first respiratory rate and flow rate of a firstnostril of the patient and a second breathing pattern indicating asecond respiratory rate and flow rate of a second nostril of thepatient; comparing the first breathing pattern and the second breathingpattern with one or more predetermined breathing patterns; anddetermining, based on comparing the first breathing pattern and thesecond breathing pattern with the one or more predetermined breathingpatterns, the position of the sensor device on the face of the patient.

Clause 66. The method of clause 65, further comprising: determining athird breathing pattern indicating a third respiratory rate or a flowrate of a mouth of the patient; determining that the third respiratoryrate or flow rate is greater than at least one of the first respiratoryrate or flow rate and the second respiratory rate or flow rate; andgenerating, based on determining that the third respiratory rate or flowrate is greater, an alert indicating a nasal cavity condition.

Clause 67. The method of clause 65, further comprising: detecting thatthe sensor device moved in a horizontal direction based on changes inthe first respiratory rate or flow rate and the second respiratory rateor flow rate.

Clause 68. The method of clause 63, further comprising: determining,based on the motion data, a physical position of the patient in thethree-dimensional space, the physical position being selected from asitting position, standing position, and lying position; determiningwhether the physical position of the patient breaches a predeterminedmedical instruction associated with the patient; and generating an alertwhen the physical position breaches the medical instruction.

Clause 69. The method of clause 63, further comprising: determining, bythe monitoring device, a geographical location of the monitoring device;and automatically modifying, by the monitoring device, based on thegeographical location of the monitoring device and a user identifiergranted access to the monitoring device, a GUI of the monitoring deviceby adding or removing one or more graphical components on the GUI.

Clause 70. The method of clause 63, further comprising: comparing themotion data with one or more predetermined motion patterns associatedwith an indication of pain; generating a pain score, by the monitoringdevice, indicating a likelihood that the patient is experiencing painbased on the comparing; and providing, by the monitoring device, fordisplay on the display device, a graphical element indicating thelikelihood that the patient is experiencing pain.

Clause 71. The method of clause 63, wherein the motion data includesaccelerometer data collected by an accelerometer embedded in the sensordevice.

Clause 72. The method of clause 64, wherein the one or morepredetermined sleep patterns comprises a predetermined movement patternof a patient's head relative to a fixed position during a predeterminedperiod of time associated with a predetermined breathing pattern for thepredetermined period of time, and wherein the apnea score is generatedbased on a strength of similarity between the predetermined movementpattern and a current movement pattern identified by the received motiondata, and the predetermined breathing pattern and a current breathingpattern identified by the received breathing data for a period of timeequivalent to the predetermined period of time.

Clause 73. A method comprising: receiving, by a monitoring device,physiological data of a patient and physical motion data indicatingmovement of the patient data from a sensor device associated with a thepatient, wherein the motion data is measured while the physiologicaldata is collected and the physical movement data are measured during asame period of time; selecting, by the monitoring device, based on thephysical movement motion data, a predetermined activity category from aplurality of predetermined activity categories; identifying, by themonitoring device, based on the selected predetermined activitycategory, a baseline physiological value from a plurality of baselinephysiological values; determining, by the monitoring device, based onthe identified baseline physiological value, a difference between avalue in the physiological data and the identified baselinephysiological value; predicting, by the monitoring device, based on thedetermined difference, a likelihood that the patient will experience aChronic Obstructive Pulmonary Disease (COPD) exacerbation within apredetermined period of time from a current time.

Clause 74. The method of clause 73, further comprising: receiving, bythe monitoring device, location data of the patient from the sensordevice, wherein the location data is measured while the physiologicaldata is collected during the same period of time; determining, by themonitoring device, based on the location data and the physical motiondata, a path traveled by the patient; identifying, by the monitoringdevice, the baseline physiological value based on the path and theselected predetermined activity category.

Clause 75. The method of clause 74, further comprising: generating, bythe monitoring device, a graphical user interface (GUI) indicating aplurality of paths traveled by the patient, wherein each path isindicated by a graphical path line and associated with the path; andproviding, by the monitoring device, the GUI for display at a displaydevice associated with the monitoring device.

Clause 76. The method of clause 75, further comprising: for each of theplurality of paths travelled by the patient: determining, by themonitoring device, a number of times the path is traveled by the patientin a recent period of time, wherein a size of the graphical path line isbased on the number of times the patient traveled the path.

Clause 77. The method of clause 75, further comprising: generating, bythe monitoring device, the plurality of baseline physiological valuesbased on physiological data measured during different earlier periods oftime; and associating, by the monitoring device, each of the pluralityof baseline physiological values with a predetermined activity categoryselected from the plurality of predetermined activity categories,wherein the predetermined activity category is selected based onphysical movement data measured during a corresponding earlier period oftime.

Clause 78. The method of clause 77, wherein each path from the pluralityof paths traveled by the patient is associated with a baselinephysiological value from the plurality of baseline physiological values,and wherein each associated baseline physiological value is generatedbased on physiological data measured during a period of time the patienttraveled the associated path.

Clause 79. The method of clause 73, further comprising: determining, bythe monitoring device, based on the physical movement data, whether thepatient travelled vertically, wherein the physical movement datacomprises accelerometer data, positional data, and orientation data; andin response to determining that the patient travelled vertically,visually indicating, by the monitoring device, a vertical movement ofthe patient in three-dimensional space.

Clause 80. A respiration sensor comprising: a housing having a firstnasal flow passage and a second nasal flow passage that extendtherethrough, wherein the first and second nasal flow passages aredisposed in parallel to one another; and an electronics board comprisinga first sensor and a second sensor, the electronics board coupled to thehousing such that the first sensor is positioned into the first nasalflow passage and the second sensor is positioned into the second nasalflow passage.

Clause 81. The respiration sensor of Clause 80, wherein the electronicsboard comprises a support structure, wherein the support structurecomprises materials with a thermal conductivity less than 0.29watt/(meter*kelvin) (W/(m*K).

Clause 82. The respiration sensor of Clause 81, wherein any of the firstor second sensors are electrically coupled to a portion of the supportstructure by one or more electrical wires.

Clause 83. The respiration sensor of Clause 82, wherein the electricalwires are traced in an undulated pattern on the support structure.

Clause 84. The respiration sensor of Clause 81, wherein a width of thesupport structure is less than 0.71 mm.

Clause 85. The respiration sensor of Clause 81, wherein a thickness ofthe support structure is less than 0.81 mm.

Clause 86. The respiration sensor of Clause 82, wherein a width of theone or more electrical wires is less than 60 micrometers.

Clause 87. The respiration sensor of Clause 82, wherein a thickness ofthe one or more electrical wires is less than 20 micrometers.

Clause 88. The respiration sensor of Clause 82, wherein a rise time ofany of the first and second sensors is 0.71° C./s.

Clause 89. The respiration sensor of Clause 82, wherein a rise time ofany of the first and second sensors is 0.32° C./s.

Clause 90. A system comprising: a first monitoring device and a firstsensor device, the first sensor device comprising a memory and one ormore processors configured to execute instructions stored on the memoryto cause the first sensor device to perform the steps in the method inclauses 44 to 52.

Clause 91. A system comprising: a sensor device and a monitoring device,the monitoring device comprising a memory and one or more processorsconfigured to execute instructions stored on the memory to cause themonitoring device to perform the steps in the method in clauses 53 to 62

Clause 92. A system comprising: a sensor device and a monitoring device,the monitoring device comprising a memory and one or more processorsconfigured to execute instructions stored on the memory to cause themonitoring device to perform the steps in the method in clauses 63 to72.

Clause 93. A system comprising: a sensor device and a monitoring device,the monitoring device comprising a memory and one or more processorsconfigured to execute instructions stored on the memory to cause themonitoring device to perform the steps in the method in clauses 73 to79.

Further Consideration

In some embodiments, any of the clauses herein may depend from any oneof the independent clauses or any one of the dependent clauses. In oneaspect, any of the clauses (e.g., dependent or independent clauses) maybe combined with any other one or more clauses (e.g., dependent orindependent clauses). In one aspect, a claim may include some or all ofthe words (e.g., steps, operations, means or components) recited in aclause, a sentence, a phrase or a paragraph. In one aspect, a claim mayinclude some or all of the words recited in one or more clauses,sentences, phrases or paragraphs. In one aspect, some of the words ineach of the clauses, sentences, phrases or paragraphs may be removed. Inone aspect, additional words or elements may be added to a clause, asentence, a phrase or a paragraph. In one aspect, the subject technologymay be implemented without utilizing some of the components, elements,functions or operations described herein. In one aspect, the subjecttechnology may be implemented utilizing additional components, elements,functions or operations.

The foregoing description is provided to enable a person skilled in theart to practice the various configurations described herein. While thesubject technology has been particularly described with reference to thevarious figures and configurations, it should be understood that theseare for illustration purposes only and should not be taken as limitingthe scope of the subject technology.

There may be many other ways to implement the subject technology.Various functions and elements described herein may be partitioneddifferently from those shown without departing from the scope of thesubject technology. Various modifications to these configurations willbe readily apparent to those skilled in the art, and generic principlesdefined herein may be applied to other configurations. Thus, manychanges and modifications may be made to the subject technology, by onehaving ordinary skill in the art, without departing from the scope ofthe subject technology.

As used herein, the phrase “at least one of” preceding a series ofitems, with the term “and” or “or” to separate any of the items,modifies the list as a whole, rather than each member of the list (i.e.,each item). The phrase “at least one of” does not require selection ofat least one of each item listed; rather, the phrase allows a meaningthat includes at least one of any one of the items, and/or at least oneof any combination of the items, and/or at least one of each of theitems. By way of example, the phrases “at least one of A, B, and C” or“at least one of A, B, or C” each refer to only A, only B, or only C;any combination of A, B, and C; and/or at least one of each of A, B, andC.

Furthermore, to the extent that the term “include,” “have,” or the likeis used in the description or the claims, such term is intended to beinclusive in a manner similar to the term “comprise” as “comprise” isinterpreted when employed as a transitional word in a claim. The word“exemplary” is used herein to mean “serving as an example, instance, orillustration.” Any embodiments described herein as “exemplary” is notnecessarily to be construed as preferred or advantageous over otherembodiments.

In one or more aspects, the terms “about,” “substantially,” and“approximately” may provide an industry-accepted tolerance for theircorresponding terms and/or relativity between items.

A reference to an element in the singular is not intended to mean “oneand only one” unless specifically stated, but rather “one or more.” Theterm “some” refers to one or more. All structural and functionalequivalents to the elements of the various configurations describedthroughout this disclosure that are known or later come to be known tothose of ordinary skill in the art are expressly incorporated herein byreference and intended to be encompassed by the subject technology.Moreover, nothing disclosed herein is intended to be dedicated to thepublic regardless of whether such disclosure is explicitly recited inthe above description.

While certain aspects and embodiments of the subject technology havebeen described, these have been presented by way of example only, andare not intended to limit the scope of the subject technology. Indeed,the novel methods and systems described herein may be embodied in avariety of other forms without departing from the spirit thereof. Theaccompanying claims and their equivalents are intended to cover suchforms or modifications as would fall within the scope and spirit of thesubject technology.

What is claimed is:
 1. A method comprising: measuring, by a first sensordevice, a physiological parameter of a patient proximate to the firstsensor device; automatically broadcasting, by the first sensor device,responsive to measuring the physiological parameter, a wirelessadvertisement signal configured to facilitate a pairing process betweenthe first sensor device and a first monitoring device; receiving, by thefirst sensor device after broadcasting the wireless advertisementsignal, a wireless request to perform the pairing process between thefirst sensor device and the first monitoring device; and automaticallycompleting the pairing process responsive to receiving the wirelessrequest.
 2. The method of claim 1, further comprising: receiving, duringthe pairing process, a patient identifier of a patient, wherein thepatient identifier is collected prior to the pairing process beinginitiated; and completing the pairing process based on receiving thepatient identifier.
 3. The method of claim 2, further comprising:automatically associating, by the first sensor device, responsive toreceiving the patient identifier, the patient identifier with anidentifier associated with the first sensor device.
 4. The method ofclaim 1, further comprising: prior to broadcasting the wirelessadvertisement signal, determining whether a value of the measuredphysiological parameter satisfies a threshold physiological parametervalue; and automatically transmitting the wireless advertisement signalwhen the value of the measured physiological parameter satisfies thethreshold physiological parameter value.
 5. The method of claim 4,wherein the value of the measured physiological parameter satisfying thethreshold physiological parameter value requires a predetermined numberof measurements of the physiological parameter being at or above apredetermined value.
 6. The method of claim 1, further comprising:receiving, at the first sensor device, data related to a colorassociated with the first sensor device from the monitoring device, anddisplaying the color on an LED of the first sensor device.
 7. The methodof claim 6, further comprising: providing, by the sensor device to themonitoring device, before receiving the data related to the color, anidentifier associated with the first sensor device, wherein the color isbased on the identifier associated with first sensor device.
 8. Themethod of claim 6, wherein the color is determined based on colorsassociated with other sensor devices within a threshold distance of thefirst sensor device.
 9. The method of claim 2, further comprising:detecting a loss of a wireless connection to the first monitoringdevice; receiving, responsive to broadcasting a second wirelessadvertisement signal, a second wireless request to perform a secondpairing process between the first sensor device and a second monitoringdevice; transmitting, immediately after completing the second pairingprocess, the patient identifier to the second monitoring device; andcausing association of the second monitoring device with the patient.10. A method, comprising: receiving a patient identifier of a firstpatient; automatically initiating, by a monitoring device, responsive toreceiving the patient identifier, a pairing process to communicativelycouple the monitoring device with a first sensor device from a pluralityof sensor devices; detecting, after the initiation of the process, awireless advertisement signal from the first sensor device, the wirelessadvertisement signal indicating that the first sensor device hasreceived a physiological parameter from a patient and is ready to bepaired to the monitoring device; pairing, responsive to the detecting,the monitoring device with the first sensor device; and receiving,responsive to the pairing, from the first sensor device, thephysiological parameter, the physiological parameter being detected bythe first sensor device prior to the monitoring device and the firstsensor device being connected.
 11. The method of claim 10, furthercomprising: receiving an identifier associated with first sensor device;determining a color associated with the first sensor device; andautomatically associating the color with the monitoring device and thefirst sensor device.
 12. The method of claim 11, further comprising:determining the color associated with the first sensor device based onthe identifier associated with the first sensor device.
 13. The methodof claim 11, further comprising: determining the color associated withthe first sensor device based on colors associated with other sensordevices of the plurality of sensor devices in a particular geographicallocation.
 14. The method of claim 11, further comprising: associatingthe color associated with the first sensor device with the patientidentifier.
 15. The method of claim 11, further comprising: transmittingdata indicating the color to the first sensor device; and causing thecolor to be displayed in a multicolor light emitting diode (LED) on thefirst sensor device.
 16. The method of claim 11, further comprising:associating one or more display components on the monitoring device withthe color associated with the first sensor device; and displaying atleast a portion of the one or more display components in the colorassociated with the first sensor device.
 17. A system, comprising: afirst monitoring device; and a first sensor device, the first sensordevice comprising a memory and one or more processors configured toexecute instructions stored on the memory to cause the first sensordevice to: measure a physiological parameter of a patient proximate tothe first sensor device; automatically broadcast, responsive tomeasuring the physiological parameter, a wireless advertisement signalconfigured to facilitate a pairing process between the first sensordevice and the monitoring device; receive, after broadcasting thewireless advertisement signal, a wireless request to perform the pairingprocess between the first sensor device and the first monitoring device;and automatically complete the pairing process responsive to receivingthe wireless request.
 18. The system of claim 17, wherein the one ormore processors are configured to execute instructions to cause thefirst sensor device to: receive, during the pairing process, a patientidentifier of a patient, wherein the patient identifier is collectedprior to the pairing process being initiated; and complete the pairingprocess based on receiving the patient identifier.
 19. The system ofclaim 18, wherein the one or more processors are configured to executeinstructions to cause the first sensor device to: automaticallyassociate, responsive to receiving the patient identifier, the patientidentifier with an identifier associated with first sensor device. 20.The system of claim 17, wherein the one or more processors areconfigured to execute instructions to cause the first sensor device to:prior to broadcasting the wireless advertisement signal, determinewhether a value of the measured physiological parameter satisfies athreshold physiological parameter value; and automatically transmit thewireless advertisement signal when the value of the measuredphysiological parameter satisfies the threshold physiological parametervalue.
 21. The system of claim 20, wherein the value of the measuredphysiological parameter satisfying the threshold physiological parametervalue requires a predetermined number of measurements of thephysiological parameter being at or above a predetermined value.
 22. Thesystem of claim 17, wherein the one or more processors are configured toexecute instructions to cause the first sensor device to: receive datarelated to a color associated with the first sensor device from themonitoring device, and displaying the color on an LED of the firstsensor device.
 23. The system of claim 22, wherein the one or moreprocessors are configured to execute instructions to cause the firstsensor device to: provide, before receiving the data related to thecolor, an identifier associated with the first sensor device, anidentifier associated with the first sensor device, wherein the color isbased on the identifier associated with first sensor device.
 24. Thesystem of claim 22, wherein the color is determined based on colorsassociated with other sensor devices within a threshold distance of thefirst sensor device.
 25. The system of claim 18, wherein the one or moreprocessors are configured to execute instructions to cause the firstsensor device to: detect a loss of a wireless connection to the firstmonitoring device; receive, responsive to broadcasting a second wirelessadvertisement signal, a second wireless request to perform a secondpairing process between the first sensor device and a second monitoringdevice; transmit, immediately after completing the second pairingprocess, the patient identifier to the second monitoring device; andcause association of the second monitoring device with the patient.